fix: update outdated CrewAI Toolkit links in docs

Update all references from the old personal repo URL
(github.com/joaomdmoura/crewai-tools) to the current monorepo location
(github.com/crewAIInc/crewAI/tree/main/lib/crewai-tools) across all
language versions (en, ko, ar, pt-BR) of the docs.

Add regression test to prevent future link rot.

Fixes #5253

Co-Authored-By: João <joao@crewai.com>

.github/workflows/vulnerability-scan.yml

@@ -0,0 +1,105 @@
+name: Vulnerability Scan
+
+on:
+  pull_request:
+  push:
+    branches: [main]
+  schedule:
+    # Run weekly on Monday at 9:00 UTC
+    - cron: '0 9 * * 1'
+
+permissions:
+  contents: read
+
+jobs:
+  pip-audit:
+    name: pip-audit
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Restore global uv cache
+        id: cache-restore
+        uses: actions/cache/restore@v4
+        with:
+          path: |
+            ~/.cache/uv
+            ~/.local/share/uv
+            .venv
+          key: uv-main-py3.11-${{ hashFiles('uv.lock') }}
+          restore-keys: |
+            uv-main-py3.11-
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v6
+        with:
+          version: "0.8.4"
+          python-version: "3.11"
+          enable-cache: false
+
+      - name: Install dependencies
+        run: uv sync --all-groups --all-extras --no-install-project
+
+      - name: Install pip-audit
+        run: uv pip install pip-audit
+
+      - name: Run pip-audit
+        run: |
+          uv run pip-audit --desc --aliases --skip-editable --format json --output pip-audit-report.json \
+            --ignore-vuln CVE-2025-69872 \
+            --ignore-vuln CVE-2026-25645 \
+            --ignore-vuln CVE-2026-27448 \
+            --ignore-vuln CVE-2026-27459 \
+            --ignore-vuln PYSEC-2023-235
+        # Ignored CVEs:
+        #   CVE-2025-69872  - diskcache 5.6.3: no fix available (latest version)
+        #   CVE-2026-25645  - requests 2.32.5: fix requires 2.33.0, blocked by crewai-tools ~=2.32.5 pin
+        #   CVE-2026-27448  - pyopenssl 25.3.0: fix requires 26.0.0, blocked by snowflake-connector-python <26.0.0 pin
+        #   CVE-2026-27459  - pyopenssl 25.3.0: same as above
+        #   PYSEC-2023-235  - couchbase: fixed in 4.6.0 (already upgraded), advisory not yet updated
+        continue-on-error: true
+
+      - name: Display results
+        if: always()
+        run: |
+          if [ -f pip-audit-report.json ]; then
+            echo "## pip-audit Results" >> $GITHUB_STEP_SUMMARY
+            echo '```json' >> $GITHUB_STEP_SUMMARY
+            cat pip-audit-report.json | python3 -m json.tool >> $GITHUB_STEP_SUMMARY
+            echo '```' >> $GITHUB_STEP_SUMMARY
+            # Fail if vulnerabilities found
+            python3 -c "
+          import json, sys
+          with open('pip-audit-report.json') as f:
+              data = json.load(f)
+          vulns = [d for d in data.get('dependencies', []) if d.get('vulns')]
+          if vulns:
+              print(f'::error::Found vulnerabilities in {len(vulns)} package(s)')
+              for v in vulns:
+                  for vuln in v['vulns']:
+                      print(f'  - {v[\"name\"]}=={v[\"version\"]}: {vuln[\"id\"]}')
+              sys.exit(1)
+          print('No known vulnerabilities found')
+          "
+          else
+            echo "::error::pip-audit failed to produce a report. Check the pip-audit step logs."
+            exit 1
+          fi
+
+      - name: Upload pip-audit report
+        if: always()
+        uses: actions/upload-artifact@v4
+        with:
+          name: pip-audit-report
+          path: pip-audit-report.json
+
+      - name: Save uv caches
+        if: steps.cache-restore.outputs.cache-hit != 'true'
+        uses: actions/cache/save@v4
+        with:
+          path: |
+            ~/.cache/uv
+            ~/.local/share/uv
+            .venv
+          key: uv-main-py3.11-${{ hashFiles('uv.lock') }}
+

docs/ar/changelog.mdx

@@ -4,6 +4,53 @@ description: "تحديثات المنتج والتحسينات وإصلاحات
 icon: "clock"
 mode: "wide"
 ---
+<Update label="2 أبريل 2026">
+  ## v1.13.0
+
+  [عرض الإصدار على GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.13.0)
+
+  ## ما الذي تغير
+
+  ### الميزات
+  - إضافة نموذج RuntimeState RootModel لتوحيد تسلسل الحالة
+  - تعزيز مستمع الأحداث مع نطاقات جديدة للقياس عن أحداث المهارة والذاكرة
+  - إضافة امتداد A2UI مع دعم v0.8/v0.9، والمخططات، والوثائق
+  - إصدار بيانات استخدام الرموز في حدث LLMCallCompletedEvent
+  - تحديث تلقائي لمستودع اختبار النشر أثناء الإصدار
+  - تحسين مرونة الإصدار المؤسسي وتجربة المستخدم
+
+  ### إصلاحات الأخطاء
+  - إضافة بيانات اعتماد مستودع الأدوات إلى تثبيت crewai
+  - إضافة بيانات اعتماد مستودع الأدوات إلى بناء uv في نشر الأدوات
+  - تمرير بيانات التعريف عبر الإعدادات بدلاً من معلمات الأدوات
+  - معالجة نماذج GPT-5.x التي لا تدعم معلمة API `stop`
+  - إضافة GPT-5 وسلسلة o إلى بادئات الرؤية متعددة الوسائط
+  - مسح ذاكرة التخزين المؤقت uv للحزم التي تم نشرها حديثًا في الإصدار المؤسسي
+  - تحديد lancedb أقل من 0.30.1 لضمان التوافق مع Windows
+  - إصلاح مستويات أذونات RBAC لتتناسب مع خيارات واجهة المستخدم الفعلية
+  - إصلاح عدم الدقة في قدرات الوكيل عبر جميع اللغات
+
+  ### الوثائق
+  - إضافة فيديو توضيحي لمهارات وكيل البرمجة إلى صفحات البدء
+  - إضافة دليل شامل لتكوين SSO
+  - إضافة مصفوفة شاملة لأذونات RBAC ودليل النشر
+  - تحديث سجل التغييرات والإصدار إلى v1.13.0
+
+  ### الأداء
+  - تقليل الحمل الزائد للإطار باستخدام حافلة الأحداث الكسولة، وتخطي التتبع عند تعطيله
+
+  ### إعادة الهيكلة
+  - تحويل Flow إلى Pydantic BaseModel
+  - تحويل فئات LLM إلى Pydantic BaseModel
+  - استبدال InstanceOf[T] بتعليقات نوع عادية
+  - إزالة دليل LLM الخاص بالطرف الثالث غير المستخدم
+
+  ## المساهمون
+
+  @alex-clawd, @dependabot[bot], @greysonlalonde, @iris-clawd, @joaomdmoura, @lorenzejay, @lucasgomide, @thiagomoretto
+
+</Update>
+
 <Update label="2 أبريل 2026">
   ## v1.13.0a7
 

docs/ar/concepts/agents.mdx

@@ -283,7 +283,7 @@ analysis_agent = Agent(
 
 يمكن تجهيز الوكلاء بأدوات متنوعة لتعزيز قدراتهم. يدعم CrewAI أدوات من:
 
-- [مجموعة أدوات CrewAI](https://github.com/joaomdmoura/crewai-tools)
+- [مجموعة أدوات CrewAI](https://github.com/crewAIInc/crewAI/tree/main/lib/crewai-tools)
 - [أدوات LangChain](https://python.langchain.com/docs/integrations/tools)
 
 إليك كيفية إضافة أدوات لوكيل:

docs/ar/concepts/tasks.mdx

@@ -796,7 +796,7 @@ print("Blog:", result)
 
 ## دمج الأدوات مع المهام
 
-استفد من أدوات [CrewAI Toolkit](https://github.com/joaomdmoura/crewai-tools) و [LangChain Tools](https://python.langchain.com/docs/integrations/tools) لتحسين أداء المهام وتفاعل الوكلاء.
+استفد من أدوات [CrewAI Toolkit](https://github.com/crewAIInc/crewAI/tree/main/lib/crewai-tools) و [LangChain Tools](https://python.langchain.com/docs/integrations/tools) لتحسين أداء المهام وتفاعل الوكلاء.
 
 ## إنشاء مهمة بأدوات
 

docs/ar/concepts/tools.mdx

@@ -17,7 +17,7 @@ mode: "wide"
 ## ما هي الأداة؟
 
 الأداة في CrewAI هي مهارة أو وظيفة يمكن للوكلاء استخدامها لأداء إجراءات مختلفة.
-يشمل ذلك أدوات من [مجموعة أدوات CrewAI](https://github.com/joaomdmoura/crewai-tools) و[أدوات LangChain](https://python.langchain.com/docs/integrations/tools)،
+يشمل ذلك أدوات من [مجموعة أدوات CrewAI](https://github.com/crewAIInc/crewAI/tree/main/lib/crewai-tools) و[أدوات LangChain](https://python.langchain.com/docs/integrations/tools)،
 مما يُمكّن كل شيء من عمليات البحث البسيطة إلى التفاعلات المعقدة والعمل الجماعي الفعال بين الوكلاء.
 
 <Note type="info" title="تحسين المؤسسات: مستودع الأدوات">

docs/ar/installation.mdx

@@ -5,6 +5,14 @@ icon: wrench
 mode: "wide"
 ---
 
+### شاهد: بناء Agents و Flows في CrewAI باستخدام Coding Agent Skills
+
+قم بتثبيت مهارات وكيل البرمجة الخاصة بنا (Claude Code، Codex، ...) لتشغيل وكلاء البرمجة بسرعة مع CrewAI.
+
+يمكنك تثبيتها باستخدام `npx skills add crewaiinc/skills`
+
+<iframe src="https://www.loom.com/embed/befb9f68b81f42ad8112bfdd95a780af" frameborder="0" webkitallowfullscreen mozallowfullscreen allowfullscreen style={{width: "100%", height: "400px"}}></iframe>
+
 ## فيديو تعليمي
 
 شاهد هذا الفيديو التعليمي لعرض تفصيلي لعملية التثبيت:

docs/ar/introduction.mdx

@@ -16,6 +16,14 @@ mode: "wide"
 
 مع أكثر من 100,000 مطور معتمد عبر دوراتنا المجتمعية، يُعد CrewAI المعيار لأتمتة الذكاء الاصطناعي الجاهزة للمؤسسات.
 
+### شاهد: بناء Agents و Flows في CrewAI باستخدام Coding Agent Skills
+
+قم بتثبيت مهارات وكيل البرمجة الخاصة بنا (Claude Code، Codex، ...) لتشغيل وكلاء البرمجة بسرعة مع CrewAI.
+
+يمكنك تثبيتها باستخدام `npx skills add crewaiinc/skills`
+
+<iframe src="https://www.loom.com/embed/befb9f68b81f42ad8112bfdd95a780af" frameborder="0" webkitallowfullscreen mozallowfullscreen allowfullscreen style={{width: "100%", height: "400px"}}></iframe>
+
 ## بنية CrewAI المعمارية
 
 صُممت بنية CrewAI لتحقيق التوازن بين الاستقلالية والتحكم.

docs/ar/quickstart.mdx

@@ -5,6 +5,14 @@ icon: rocket
 mode: "wide"
 ---
 
+### شاهد: بناء Agents و Flows في CrewAI باستخدام Coding Agent Skills
+
+قم بتثبيت مهارات وكيل البرمجة الخاصة بنا (Claude Code، Codex، ...) لتشغيل وكلاء البرمجة بسرعة مع CrewAI.
+
+يمكنك تثبيتها باستخدام `npx skills add crewaiinc/skills`
+
+<iframe src="https://www.loom.com/embed/befb9f68b81f42ad8112bfdd95a780af" frameborder="0" webkitallowfullscreen mozallowfullscreen allowfullscreen style={{width: "100%", height: "400px"}}></iframe>
+
 ## ابنِ أول وكيل CrewAI
 
 لننشئ طاقماً بسيطاً يساعدنا في `البحث` و`إعداد التقارير` عن `أحدث تطورات الذكاء الاصطناعي` لموضوع أو مجال معين.

docs/en/changelog.mdx

@@ -4,6 +4,53 @@ description: "Product updates, improvements, and bug fixes for CrewAI"
 icon: "clock"
 mode: "wide"
 ---
+<Update label="Apr 02, 2026">
+  ## v1.13.0
+
+  [View release on GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.13.0)
+
+  ## What's Changed
+
+  ### Features
+  - Add RuntimeState RootModel for unified state serialization
+  - Enhance event listener with new telemetry spans for skill and memory events
+  - Add A2UI extension with v0.8/v0.9 support, schemas, and docs
+  - Emit token usage data in LLMCallCompletedEvent
+  - Auto-update deployment test repo during release
+  - Improve enterprise release resilience and UX
+
+  ### Bug Fixes
+  - Add tool repository credentials to crewai install
+  - Add tool repository credentials to uv build in tool publish
+  - Pass fingerprint metadata via config instead of tool args
+  - Handle GPT-5.x models not supporting the `stop` API parameter
+  - Add GPT-5 and o-series to multimodal vision prefixes
+  - Bust uv cache for freshly published packages in enterprise release
+  - Cap lancedb below 0.30.1 for Windows compatibility
+  - Fix RBAC permission levels to match actual UI options
+  - Fix inaccuracies in agent-capabilities across all languages
+
+  ### Documentation
+  - Add coding agent skills demo video to getting started pages
+  - Add comprehensive SSO configuration guide
+  - Add comprehensive RBAC permissions matrix and deployment guide
+  - Update changelog and version for v1.13.0
+
+  ### Performance
+  - Reduce framework overhead with lazy event bus, skip tracing when disabled
+
+  ### Refactoring
+  - Convert Flow to Pydantic BaseModel
+  - Convert LLM classes to Pydantic BaseModel
+  - Replace InstanceOf[T] with plain type annotations
+  - Remove unused third_party LLM directory
+
+  ## Contributors
+
+  @alex-clawd, @dependabot[bot], @greysonlalonde, @iris-clawd, @joaomdmoura, @lorenzejay, @lucasgomide, @thiagomoretto
+
+</Update>
+
 <Update label="Apr 02, 2026">
   ## v1.13.0a7
 

docs/en/concepts/agents.mdx

@@ -347,7 +347,7 @@ multimodal_agent = Agent(
 
 Agents can be equipped with various tools to enhance their capabilities. CrewAI supports tools from:
 
-- [CrewAI Toolkit](https://github.com/joaomdmoura/crewai-tools)
+- [CrewAI Toolkit](https://github.com/crewAIInc/crewAI/tree/main/lib/crewai-tools)
 - [LangChain Tools](https://python.langchain.com/docs/integrations/tools)
 
 Here's how to add tools to an agent:

docs/en/concepts/tasks.mdx

@@ -797,7 +797,7 @@ By using output_pydantic or output_json, you ensure that your tasks produce outp
 
 ## Integrating Tools with Tasks
 
-Leverage tools from the [CrewAI Toolkit](https://github.com/joaomdmoura/crewai-tools) and [LangChain Tools](https://python.langchain.com/docs/integrations/tools) for enhanced task performance and agent interaction.
+Leverage tools from the [CrewAI Toolkit](https://github.com/crewAIInc/crewAI/tree/main/lib/crewai-tools) and [LangChain Tools](https://python.langchain.com/docs/integrations/tools) for enhanced task performance and agent interaction.
 
 ## Creating a Task with Tools
 

docs/en/concepts/tools.mdx

@@ -17,7 +17,7 @@ This documentation outlines how to create, integrate, and leverage these tools w
 ## What is a Tool?
 
 A tool in CrewAI is a skill or function that agents can utilize to perform various actions.
-This includes tools from the [CrewAI Toolkit](https://github.com/joaomdmoura/crewai-tools) and [LangChain Tools](https://python.langchain.com/docs/integrations/tools),
+This includes tools from the [CrewAI Toolkit](https://github.com/crewAIInc/crewAI/tree/main/lib/crewai-tools) and [LangChain Tools](https://python.langchain.com/docs/integrations/tools),
 enabling everything from simple searches to complex interactions and effective teamwork among agents.
 
 <Note type="info" title="Enterprise Enhancement: Tools Repository">

docs/en/installation.mdx

@@ -5,6 +5,14 @@ icon: wrench
 mode: "wide"
 ---
 
+### Watch: Building CrewAI Agents & Flows with Coding Agent Skills
+
+Install our coding agent skills (Claude Code, Codex, ...) to quickly get your coding agents up and running with CrewAI.
+
+You can install it with `npx skills add crewaiinc/skills`
+
+<iframe src="https://www.loom.com/embed/befb9f68b81f42ad8112bfdd95a780af" frameborder="0" webkitallowfullscreen mozallowfullscreen allowfullscreen style={{width: "100%", height: "400px"}}></iframe>
+
 ## Video Tutorial
 
 Watch this video tutorial for a step-by-step demonstration of the installation process:

docs/en/introduction.mdx

@@ -16,6 +16,14 @@ It empowers developers to build production-ready multi-agent systems by combinin
 
 With over 100,000 developers certified through our community courses, CrewAI is the standard for enterprise-ready AI automation.
 
+### Watch: Building CrewAI Agents & Flows with Coding Agent Skills
+
+Install our coding agent skills (Claude Code, Codex, ...) to quickly get your coding agents up and running with CrewAI.
+
+You can install it with `npx skills add crewaiinc/skills`
+
+<iframe src="https://www.loom.com/embed/befb9f68b81f42ad8112bfdd95a780af" frameborder="0" webkitallowfullscreen mozallowfullscreen allowfullscreen style={{width: "100%", height: "400px"}}></iframe>
+
 ## The CrewAI Architecture
 
 CrewAI's architecture is designed to balance autonomy with control.

docs/en/quickstart.mdx

@@ -5,6 +5,14 @@ icon: rocket
 mode: "wide"
 ---
 
+### Watch: Building CrewAI Agents & Flows with Coding Agent Skills
+
+Install our coding agent skills (Claude Code, Codex, ...) to quickly get your coding agents up and running with CrewAI.
+
+You can install it with `npx skills add crewaiinc/skills`
+
+<iframe src="https://www.loom.com/embed/befb9f68b81f42ad8112bfdd95a780af" frameborder="0" webkitallowfullscreen mozallowfullscreen allowfullscreen style={{width: "100%", height: "400px"}}></iframe>
+
 ## Build your first CrewAI Agent
 
 Let's create a simple crew that will help us `research` and `report` on the `latest AI developments` for a given topic or subject.

docs/ko/changelog.mdx

@@ -4,6 +4,53 @@ description: "CrewAI의 제품 업데이트, 개선 사항 및 버그 수정"
 icon: "clock"
 mode: "wide"
 ---
+<Update label="2026년 4월 2일">
+  ## v1.13.0
+
+  [GitHub 릴리스 보기](https://github.com/crewAIInc/crewAI/releases/tag/1.13.0)
+
+  ## 변경 사항
+
+  ### 기능
+  - 통합 상태 직렬화를 위한 RuntimeState RootModel 추가
+  - 기술 및 메모리 이벤트에 대한 새로운 텔레메트리 스팬으로 이벤트 리스너 강화
+  - v0.8/v0.9 지원, 스키마 및 문서가 포함된 A2UI 확장 추가
+  - LLMCallCompletedEvent에서 토큰 사용 데이터 방출
+  - 릴리스 중 배포 테스트 리포 자동 업데이트
+  - 기업 릴리스의 복원력 및 사용자 경험 개선
+
+  ### 버그 수정
+  - crewai 설치에 도구 리포지토리 자격 증명 추가
+  - 도구 게시의 uv 빌드에 도구 리포지토리 자격 증명 추가
+  - 도구 인수 대신 구성으로 지문 메타데이터 전달
+  - `stop` API 매개변수를 지원하지 않는 GPT-5.x 모델 처리
+  - 멀티모달 비전 접두사에 GPT-5 및 o-series 추가
+  - 기업 릴리스에서 새로 게시된 패키지에 대한 uv 캐시 무효화
+  - Windows 호환성을 위해 lancedb를 0.30.1 이하로 제한
+  - 실제 UI 옵션과 일치하도록 RBAC 권한 수준 수정
+  - 모든 언어에서 에이전트 기능의 부정확성 수정
+
+  ### 문서
+  - 시작하기 페이지에 코딩 에이전트 기술 데모 비디오 추가
+  - 포괄적인 SSO 구성 가이드 추가
+  - 포괄적인 RBAC 권한 매트릭스 및 배포 가이드 추가
+  - v1.13.0에 대한 변경 로그 및 버전 업데이트
+
+  ### 성능
+  - 비활성화 시 추적 건너뛰기와 함께 지연 이벤트 버스를 사용하여 프레임워크 오버헤드 감소
+
+  ### 리팩토링
+  - Flow를 Pydantic BaseModel로 변환
+  - LLM 클래스를 Pydantic BaseModel로 변환
+  - InstanceOf[T]를 일반 타입 주석으로 교체
+  - 사용되지 않는 third_party LLM 디렉토리 제거
+
+  ## 기여자
+
+  @alex-clawd, @dependabot[bot], @greysonlalonde, @iris-clawd, @joaomdmoura, @lorenzejay, @lucasgomide, @thiagomoretto
+
+</Update>
+
 <Update label="2026년 4월 2일">
   ## v1.13.0a7
 

docs/ko/concepts/agents.mdx

@@ -322,7 +322,7 @@ multimodal_agent = Agent(
 ## 에이전트 도구
 
 에이전트는 다양한 도구를 장착하여 그 능력을 향상시킬 수 있습니다. CrewAI는 다음의 도구들을 지원합니다:
-- [CrewAI Toolkit](https://github.com/joaomdmoura/crewai-tools)
+- [CrewAI Toolkit](https://github.com/crewAIInc/crewAI/tree/main/lib/crewai-tools)
 - [LangChain Tools](https://python.langchain.com/docs/integrations/tools)
 
 에이전트에 도구를 추가하는 방법은 다음과 같습니다:

docs/ko/concepts/tasks.mdx

@@ -616,7 +616,7 @@ output_pydantic 또는 output_json을 사용하면, 작업의 출력이 일관
 
 ## 도구와 작업 통합
 
-향상된 작업 성능과 에이전트 상호작용을 위해 [CrewAI Toolkit](https://github.com/joaomdmoura/crewai-tools) 및 [LangChain Tools](https://python.langchain.com/docs/integrations/tools)의 도구를 활용하세요.
+향상된 작업 성능과 에이전트 상호작용을 위해 [CrewAI Toolkit](https://github.com/crewAIInc/crewAI/tree/main/lib/crewai-tools) 및 [LangChain Tools](https://python.langchain.com/docs/integrations/tools)의 도구를 활용하세요.
 
 ## 도구와 함께 Task 생성하기
 

docs/ko/concepts/tools.mdx

@@ -17,7 +17,7 @@ CrewAI 도구는 에이전트에게 웹 검색, 데이터 분석부터 동료
 ## Tool이란 무엇인가?
 
 CrewAI에서 tool은 에이전트가 다양한 작업을 수행하기 위해 활용할 수 있는 기술 또는 기능입니다.
-이에는 [CrewAI Toolkit](https://github.com/joaomdmoura/crewai-tools) 및 [LangChain Tools](https://python.langchain.com/docs/integrations/tools)의 tool이 포함되어,
+이에는 [CrewAI Toolkit](https://github.com/crewAIInc/crewAI/tree/main/lib/crewai-tools) 및 [LangChain Tools](https://python.langchain.com/docs/integrations/tools)의 tool이 포함되어,
 간단한 검색부터 복잡한 상호작용, 그리고 에이전트 간의 효과적인 협업까지 모두 가능하게 합니다.
 
 <Note type="info" title="엔터프라이즈 확장: Tools Repository">
@@ -284,4 +284,4 @@ writer1 = Agent(
 
 ## 결론
 
-도구는 CrewAI 에이전트의 역량을 확장하는 데 중요한 역할을 하며, 이를 통해 에이전트가 폭넓은 작업을 수행하고 효과적으로 협업할 수 있습니다. CrewAI로 솔루션을 구축할 때는, 맞춤형 또는 기존의 도구를 모두 활용하여 에이전트를 강화하고 AI 생태계를 향상시키세요. 에이전트의 성능과 기능을 최적화하기 위해 오류 처리, 캐싱 메커니즘, 그리고 도구 인자의 유연성도 고려해보시기 바랍니다.
+도구는 CrewAI 에이전트의 역량을 확장하는 데 중요한 역할을 하며, 이를 통해 에이전트가 폭넓은 작업을 수행하고 효과적으로 협업할 수 있습니다. CrewAI로 솔루션을 구축할 때는, 맞춤형 또는 기존의 도구를 모두 활용하여 에이전트를 강화하고 AI 생태계를 향상시키세요. 에이전트의 성능과 기능을 최적화하기 위해 오류 처리, 캐싱 메커니즘, 그리고 도구 인자의 유연성도 고려해보시기 바랍니다.

docs/ko/installation.mdx

@@ -5,6 +5,14 @@ icon: wrench
 mode: "wide"
 ---
 
+### 영상: 코딩 에이전트 스킬을 활용한 CrewAI Agents & Flows 구축
+
+코딩 에이전트 스킬(Claude Code, Codex 등)을 설치하여 CrewAI로 코딩 에이전트를 빠르게 시작하세요.
+
+`npx skills add crewaiinc/skills` 명령어로 설치할 수 있습니다
+
+<iframe src="https://www.loom.com/embed/befb9f68b81f42ad8112bfdd95a780af" frameborder="0" webkitallowfullscreen mozallowfullscreen allowfullscreen style={{width: "100%", height: "400px"}}></iframe>
+
 ## 비디오 튜토리얼
 
 설치 과정을 단계별로 시연하는 비디오 튜토리얼을 시청하세요:

docs/ko/introduction.mdx

@@ -16,6 +16,14 @@ mode: "wide"
 
 10만 명이 넘는 개발자가 커뮤니티 과정을 통해 인증을 받았으며, CrewAI는 기업용 AI 자동화의 표준입니다.
 
+### 영상: 코딩 에이전트 스킬을 활용한 CrewAI Agents & Flows 구축
+
+코딩 에이전트 스킬(Claude Code, Codex 등)을 설치하여 CrewAI로 코딩 에이전트를 빠르게 시작하세요.
+
+`npx skills add crewaiinc/skills` 명령어로 설치할 수 있습니다
+
+<iframe src="https://www.loom.com/embed/befb9f68b81f42ad8112bfdd95a780af" frameborder="0" webkitallowfullscreen mozallowfullscreen allowfullscreen style={{width: "100%", height: "400px"}}></iframe>
+
 ## CrewAI 아키텍처
 
 CrewAI의 아키텍처는 자율성과 제어의 균형을 맞추도록 설계되었습니다.

docs/ko/quickstart.mdx

@@ -5,6 +5,14 @@ icon: rocket
 mode: "wide"
 ---
 
+### 영상: 코딩 에이전트 스킬을 활용한 CrewAI Agents & Flows 구축
+
+코딩 에이전트 스킬(Claude Code, Codex 등)을 설치하여 CrewAI로 코딩 에이전트를 빠르게 시작하세요.
+
+`npx skills add crewaiinc/skills` 명령어로 설치할 수 있습니다
+
+<iframe src="https://www.loom.com/embed/befb9f68b81f42ad8112bfdd95a780af" frameborder="0" webkitallowfullscreen mozallowfullscreen allowfullscreen style={{width: "100%", height: "400px"}}></iframe>
+
 ## 첫 번째 CrewAI Agent 만들기
 
 이제 주어진 주제나 항목에 대해 `최신 AI 개발 동향`을 `연구`하고 `보고`하는 간단한 crew를 만들어보겠습니다.

docs/pt-BR/changelog.mdx

@@ -4,6 +4,53 @@ description: "Atualizações de produto, melhorias e correções do CrewAI"
 icon: "clock"
 mode: "wide"
 ---
+<Update label="02 abr 2026">
+  ## v1.13.0
+
+  [Ver release no GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.13.0)
+
+  ## O que Mudou
+
+  ### Funcionalidades
+  - Adicionar RuntimeState RootModel para serialização de estado unificado
+  - Melhorar o listener de eventos com novos spans de telemetria para eventos de habilidade e memória
+  - Adicionar extensão A2UI com suporte a v0.8/v0.9, esquemas e documentação
+  - Emitir dados de uso de token no LLMCallCompletedEvent
+  - Atualizar automaticamente o repositório de testes de implantação durante o lançamento
+  - Melhorar a resiliência e a experiência do usuário na versão empresarial
+
+  ### Correções de Bugs
+  - Adicionar credenciais do repositório de ferramentas ao crewai install
+  - Adicionar credenciais do repositório de ferramentas ao uv build na publicação de ferramentas
+  - Passar metadados de impressão digital via configuração em vez de argumentos de ferramenta
+  - Lidar com modelos GPT-5.x que não suportam o parâmetro API `stop`
+  - Adicionar GPT-5 e a série o aos prefixos de visão multimodal
+  - Limpar cache uv para pacotes recém-publicados na versão empresarial
+  - Limitar lancedb abaixo de 0.30.1 para compatibilidade com Windows
+  - Corrigir níveis de permissão RBAC para corresponder às opções reais da interface do usuário
+  - Corrigir imprecisões nas capacidades do agente em todos os idiomas
+
+  ### Documentação
+  - Adicionar vídeo de demonstração de habilidades do agente de codificação às páginas de introdução
+  - Adicionar guia abrangente de configuração SSO
+  - Adicionar matriz de permissões RBAC abrangente e guia de implantação
+  - Atualizar changelog e versão para v1.13.0
+
+  ### Desempenho
+  - Reduzir a sobrecarga do framework com bus de eventos preguiçoso, pular rastreamento quando desativado
+
+  ### Refatoração
+  - Converter Flow para Pydantic BaseModel
+  - Converter classes LLM para Pydantic BaseModel
+  - Substituir InstanceOf[T] por anotações de tipo simples
+  - Remover diretório LLM de terceiros não utilizado
+
+  ## Contribuidores
+
+  @alex-clawd, @dependabot[bot], @greysonlalonde, @iris-clawd, @joaomdmoura, @lorenzejay, @lucasgomide, @thiagomoretto
+
+</Update>
+
 <Update label="02 abr 2026">
   ## v1.13.0a7
 

docs/pt-BR/concepts/agents.mdx

@@ -344,7 +344,7 @@ multimodal_agent = Agent(
 
 Agentes podem ser equipados com diversas ferramentas para ampliar suas capacidades. O CrewAI suporta ferramentas do:
 
-- [CrewAI Toolkit](https://github.com/joaomdmoura/crewai-tools)
+- [CrewAI Toolkit](https://github.com/crewAIInc/crewAI/tree/main/lib/crewai-tools)
 - [LangChain Tools](https://python.langchain.com/docs/integrations/tools)
 
 Veja como adicionar ferramentas a um agente:

docs/pt-BR/concepts/tasks.mdx

@@ -637,7 +637,7 @@ Utilizando `output_pydantic` ou `output_json`, você garante que suas tarefas pr
 
 ## Integrando Ferramentas com Tarefas
 
-Utilize ferramentas do [CrewAI Toolkit](https://github.com/joaomdmoura/crewai-tools) e [LangChain Tools](https://python.langchain.com/docs/integrations/tools) para ampliar o desempenho das tarefas e aprimorar a interação dos agentes.
+Utilize ferramentas do [CrewAI Toolkit](https://github.com/crewAIInc/crewAI/tree/main/lib/crewai-tools) e [LangChain Tools](https://python.langchain.com/docs/integrations/tools) para ampliar o desempenho das tarefas e aprimorar a interação dos agentes.
 
 ## Criando uma Tarefa com Ferramentas
 

docs/pt-BR/concepts/tools.mdx

@@ -17,7 +17,7 @@ Esta documentação descreve como criar, integrar e aproveitar essas ferramentas
 ## O que é uma Ferramenta?
 
 Uma ferramenta no CrewAI é uma habilidade ou função que os agentes podem utilizar para executar diversas ações.
-Isso inclui ferramentas do [CrewAI Toolkit](https://github.com/joaomdmoura/crewai-tools) e [LangChain Tools](https://python.langchain.com/docs/integrations/tools),
+Isso inclui ferramentas do [CrewAI Toolkit](https://github.com/crewAIInc/crewAI/tree/main/lib/crewai-tools) e [LangChain Tools](https://python.langchain.com/docs/integrations/tools),
 permitindo desde buscas simples até interações complexas e trabalho em equipe eficiente entre agentes.
 
 <Note type="info" title="Aprimoramento para Empresas: Repositório de Ferramentas">

docs/pt-BR/installation.mdx

@@ -5,6 +5,14 @@ icon: wrench
 mode: "wide"
 ---
 
+### Assista: Construindo Agents e Flows CrewAI com Coding Agent Skills
+
+Instale nossas coding agent skills (Claude Code, Codex, ...) para colocar seus agentes de código para funcionar rapidamente com o CrewAI.
+
+Você pode instalar com `npx skills add crewaiinc/skills`
+
+<iframe src="https://www.loom.com/embed/befb9f68b81f42ad8112bfdd95a780af" frameborder="0" webkitallowfullscreen mozallowfullscreen allowfullscreen style={{width: "100%", height: "400px"}}></iframe>
+
 ## Tutorial em Vídeo
 
 Assista a este tutorial em vídeo para uma demonstração passo a passo do processo de instalação:

docs/pt-BR/introduction.mdx

@@ -16,6 +16,14 @@ Ele capacita desenvolvedores a construir sistemas multi-agente prontos para prod
 
 Com mais de 100.000 desenvolvedores certificados em nossos cursos comunitários, o CrewAI é o padrão para automação de IA pronta para empresas.
 
+### Assista: Construindo Agents e Flows CrewAI com Coding Agent Skills
+
+Instale nossas coding agent skills (Claude Code, Codex, ...) para colocar seus agentes de código para funcionar rapidamente com o CrewAI.
+
+Você pode instalar com `npx skills add crewaiinc/skills`
+
+<iframe src="https://www.loom.com/embed/befb9f68b81f42ad8112bfdd95a780af" frameborder="0" webkitallowfullscreen mozallowfullscreen allowfullscreen style={{width: "100%", height: "400px"}}></iframe>
+
 ## A Arquitetura do CrewAI
 
 A arquitetura do CrewAI foi projetada para equilibrar autonomia com controle.

docs/pt-BR/quickstart.mdx

@@ -5,6 +5,14 @@ icon: rocket
 mode: "wide"
 ---
 
+### Assista: Construindo Agents e Flows CrewAI com Coding Agent Skills
+
+Instale nossas coding agent skills (Claude Code, Codex, ...) para colocar seus agentes de código para funcionar rapidamente com o CrewAI.
+
+Você pode instalar com `npx skills add crewaiinc/skills`
+
+<iframe src="https://www.loom.com/embed/befb9f68b81f42ad8112bfdd95a780af" frameborder="0" webkitallowfullscreen mozallowfullscreen allowfullscreen style={{width: "100%", height: "400px"}}></iframe>
+
 ## Construa seu primeiro Agente CrewAI
 
 Vamos criar uma tripulação simples que nos ajudará a `pesquisar` e `relatar` sobre os `últimos avanços em IA` para um determinado tópico ou assunto.

lib/crewai-files/src/crewai_files/__init__.py

@@ -152,4 +152,4 @@ __all__ = [
     "wrap_file_source",
 ]
 
-__version__ = "1.13.0a7"
+__version__ = "1.13.0"

lib/crewai-tools/pyproject.toml

@@ -11,7 +11,7 @@ dependencies = [
     "pytube~=15.0.0",
     "requests~=2.32.5",
     "docker~=7.1.0",
-    "crewai==1.13.0a7",
+    "crewai==1.13.0",
     "tiktoken~=0.8.0",
     "beautifulsoup4~=4.13.4",
     "python-docx~=1.2.0",

lib/crewai-tools/src/crewai_tools/__init__.py

@@ -309,4 +309,4 @@ __all__ = [
     "ZapierActionTools",
 ]
 
-__version__ = "1.13.0a7"
+__version__ = "1.13.0"

lib/crewai/pyproject.toml

@@ -54,7 +54,7 @@ Repository = "https://github.com/crewAIInc/crewAI"
 
 [project.optional-dependencies]
 tools = [
-    "crewai-tools==1.13.0a7",
+    "crewai-tools==1.13.0",
 ]
 embeddings = [
     "tiktoken~=0.8.0"

lib/crewai/src/crewai/__init__.py

@@ -8,14 +8,15 @@ from pydantic import PydanticUserError
 
 from crewai.agent.core import Agent
 from crewai.agent.planning_config import PlanningConfig
+from crewai.context import ExecutionContext
 from crewai.crew import Crew
 from crewai.crews.crew_output import CrewOutput
-from crewai.execution_context import ExecutionContext
 from crewai.flow.flow import Flow
 from crewai.knowledge.knowledge import Knowledge
 from crewai.llm import LLM
 from crewai.llms.base_llm import BaseLLM
 from crewai.process import Process
+from crewai.runtime_state import _entity_discriminator
 from crewai.task import Task
 from crewai.tasks.llm_guardrail import LLMGuardrail
 from crewai.tasks.task_output import TaskOutput
@@ -45,7 +46,7 @@ def _suppress_pydantic_deprecation_warnings() -> None:
 
 _suppress_pydantic_deprecation_warnings()
 
-__version__ = "1.13.0a7"
+__version__ = "1.13.0"
 _telemetry_submitted = False
 
 
@@ -112,10 +113,13 @@ try:
 
     _base_namespace: dict[str, type] = {
         "Agent": Agent,
+        "BaseAgent": _BaseAgent,
         "Crew": Crew,
+        "Flow": Flow,
         "BaseLLM": BaseLLM,
         "Task": Task,
         "CrewAgentExecutorMixin": _CrewAgentExecutorMixin,
+        "ExecutionContext": ExecutionContext,
     }
 
     try:
@@ -154,13 +158,34 @@ try:
     for _mod_name in (
         _BaseAgent.__module__,
         Agent.__module__,
+        Crew.__module__,
+        Flow.__module__,
+        Task.__module__,
         _AgentExecutor.__module__,
     ):
         sys.modules[_mod_name].__dict__.update(_resolve_namespace)
 
+    from crewai.tasks.conditional_task import ConditionalTask as _ConditionalTask
+
     _BaseAgent.model_rebuild(force=True, _types_namespace=_full_namespace)
+    Task.model_rebuild(force=True, _types_namespace=_full_namespace)
+    _ConditionalTask.model_rebuild(force=True, _types_namespace=_full_namespace)
+    Crew.model_rebuild(force=True, _types_namespace=_full_namespace)
+    Flow.model_rebuild(force=True, _types_namespace=_full_namespace)
     _AgentExecutor.model_rebuild(force=True, _types_namespace=_full_namespace)
 
+    from typing import Annotated
+
+    from pydantic import Discriminator, RootModel, Tag
+
+    Entity = Annotated[
+        Annotated[Flow, Tag("flow")]  # type: ignore[type-arg]
+        | Annotated[Crew, Tag("crew")]
+        | Annotated[Agent, Tag("agent")],
+        Discriminator(_entity_discriminator),
+    ]
+    RuntimeState = RootModel[list[Entity]]
+
     try:
         Agent.model_rebuild(force=True, _types_namespace=_full_namespace)
     except PydanticUserError:
@@ -172,6 +197,7 @@ except (ImportError, PydanticUserError):
         "model_rebuild() failed; forward refs may be unresolved.",
         exc_info=True,
     )
+    RuntimeState = None  # type: ignore[assignment,misc]
 
 __all__ = [
     "LLM",
@@ -186,6 +212,7 @@ __all__ = [
     "Memory",
     "PlanningConfig",
     "Process",
+    "RuntimeState",
     "Task",
     "TaskOutput",
     "__version__",

lib/crewai/src/crewai/agent/core.py

@@ -14,6 +14,7 @@ import subprocess
 import time
 from typing import (
     TYPE_CHECKING,
+    Annotated,
     Any,
     Literal,
     NoReturn,
@@ -23,12 +24,14 @@ import warnings
 
 from pydantic import (
     BaseModel,
+    BeforeValidator,
     ConfigDict,
     Field,
     InstanceOf,
     PrivateAttr,
     model_validator,
 )
+from pydantic.functional_serializers import PlainSerializer
 from typing_extensions import Self
 
 from crewai.agent.planning_config import PlanningConfig
@@ -46,7 +49,11 @@ from crewai.agent.utils import (
     save_last_messages,
     validate_max_execution_time,
 )
-from crewai.agents.agent_builder.base_agent import BaseAgent
+from crewai.agents.agent_builder.base_agent import (
+    BaseAgent,
+    _serialize_llm_ref,
+    _validate_llm_ref,
+)
 from crewai.agents.cache.cache_handler import CacheHandler
 from crewai.agents.crew_agent_executor import CrewAgentExecutor
 from crewai.events.event_bus import crewai_event_bus
@@ -122,6 +129,24 @@ if TYPE_CHECKING:
 
 _passthrough_exceptions: tuple[type[Exception], ...] = ()
 
+_EXECUTOR_CLASS_MAP: dict[str, type] = {
+    "CrewAgentExecutor": CrewAgentExecutor,
+    "AgentExecutor": AgentExecutor,
+}
+
+
+def _validate_executor_class(value: Any) -> Any:
+    if isinstance(value, str):
+        cls = _EXECUTOR_CLASS_MAP.get(value)
+        if cls is None:
+            raise ValueError(f"Unknown executor class: {value}")
+        return cls
+    return value
+
+
+def _serialize_executor_class(value: Any) -> str:
+    return value.__name__ if isinstance(value, type) else str(value)
+
 
 class Agent(BaseAgent):
     """Represents an agent in a system.
@@ -167,12 +192,16 @@ class Agent(BaseAgent):
         default=True,
         description="Use system prompt for the agent.",
     )
-    llm: str | BaseLLM | None = Field(
-        description="Language model that will run the agent.", default=None
-    )
-    function_calling_llm: str | BaseLLM | None = Field(
-        description="Language model that will run the agent.", default=None
-    )
+    llm: Annotated[
+        str | BaseLLM | None,
+        BeforeValidator(_validate_llm_ref),
+        PlainSerializer(_serialize_llm_ref, return_type=str | None, when_used="json"),
+    ] = Field(description="Language model that will run the agent.", default=None)
+    function_calling_llm: Annotated[
+        str | BaseLLM | None,
+        BeforeValidator(_validate_llm_ref),
+        PlainSerializer(_serialize_llm_ref, return_type=str | None, when_used="json"),
+    ] = Field(description="Language model that will run the agent.", default=None)
     system_template: str | None = Field(
         default=None, description="System format for the agent."
     )
@@ -271,7 +300,11 @@ class Agent(BaseAgent):
     agent_executor: InstanceOf[CrewAgentExecutor] | InstanceOf[AgentExecutor] | None = (
         Field(default=None, description="An instance of the CrewAgentExecutor class.")
     )
-    executor_class: type[CrewAgentExecutor] | type[AgentExecutor] = Field(
+    executor_class: Annotated[
+        type[CrewAgentExecutor] | type[AgentExecutor],
+        BeforeValidator(_validate_executor_class),
+        PlainSerializer(_serialize_executor_class, return_type=str, when_used="json"),
+    ] = Field(
         default=CrewAgentExecutor,
         description="Class to use for the agent executor. Defaults to CrewAgentExecutor, can optionally use AgentExecutor.",
     )
@@ -1053,7 +1086,7 @@ class Agent(BaseAgent):
                 )
             )
 
-    def get_delegation_tools(self, agents: list[BaseAgent]) -> list[BaseTool]:
+    def get_delegation_tools(self, agents: Sequence[BaseAgent]) -> list[BaseTool]:
         agent_tools = AgentTools(agents=agents)
         return agent_tools.tools()
 

lib/crewai/src/crewai/agents/agent_adapters/langgraph/langgraph_adapter.py

@@ -5,7 +5,7 @@ with CrewAI's agent system. Provides memory persistence, tool integration, and s
 output functionality.
 """
 
-from collections.abc import Callable
+from collections.abc import Callable, Sequence
 from typing import Any, cast
 
 from pydantic import ConfigDict, Field, PrivateAttr
@@ -30,6 +30,7 @@ from crewai.events.types.agent_events import (
 )
 from crewai.tools.agent_tools.agent_tools import AgentTools
 from crewai.tools.base_tool import BaseTool
+from crewai.types.callback import SerializableCallable
 from crewai.utilities import Logger
 from crewai.utilities.converter import Converter
 from crewai.utilities.import_utils import require
@@ -50,7 +51,7 @@ class LangGraphAgentAdapter(BaseAgentAdapter):
     _memory: Any = PrivateAttr(default=None)
     _max_iterations: int = PrivateAttr(default=10)
     function_calling_llm: Any = Field(default=None)
-    step_callback: Callable[..., Any] | None = Field(default=None)
+    step_callback: SerializableCallable | None = Field(default=None)
 
     model: str = Field(default="gpt-4o")
     verbose: bool = Field(default=False)
@@ -272,7 +273,7 @@ class LangGraphAgentAdapter(BaseAgentAdapter):
             available_tools: list[Any] = self._tool_adapter.tools()
             self._graph.tools = available_tools
 
-    def get_delegation_tools(self, agents: list[BaseAgent]) -> list[BaseTool]:
+    def get_delegation_tools(self, agents: Sequence[BaseAgent]) -> list[BaseTool]:
         """Implement delegation tools support for LangGraph.
 
         Creates delegation tools that allow this agent to delegate tasks to other agents.

lib/crewai/src/crewai/agents/agent_adapters/openai_agents/openai_adapter.py

@@ -4,6 +4,7 @@ This module contains the OpenAIAgentAdapter class that integrates OpenAI Assista
 with CrewAI's agent system, providing tool integration and structured output support.
 """
 
+from collections.abc import Sequence
 from typing import Any, cast
 
 from pydantic import ConfigDict, Field, PrivateAttr
@@ -221,7 +222,7 @@ class OpenAIAgentAdapter(BaseAgentAdapter):
         """
         return self._converter_adapter.post_process_result(result.final_output)
 
-    def get_delegation_tools(self, agents: list[BaseAgent]) -> list[BaseTool]:
+    def get_delegation_tools(self, agents: Sequence[BaseAgent]) -> list[BaseTool]:
         """Implement delegation tools support.
 
         Creates delegation tools that allow this agent to delegate tasks to other agents.

lib/crewai/src/crewai/agents/agent_builder/base_agent.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 from abc import ABC, abstractmethod
+from collections.abc import Sequence
 from copy import copy as shallow_copy
 from hashlib import md5
 from pathlib import Path
@@ -48,6 +49,7 @@ from crewai.utilities.string_utils import interpolate_only
 
 
 if TYPE_CHECKING:
+    from crewai.context import ExecutionContext
     from crewai.crew import Crew
 
 
@@ -61,6 +63,26 @@ def _serialize_crew_ref(value: Any) -> str | None:
     return str(value.id) if hasattr(value, "id") else str(value)
 
 
+def _validate_llm_ref(value: Any) -> Any:
+    return value
+
+
+def _resolve_agent(value: Any, info: Any) -> Any:
+    if isinstance(value, BaseAgent) or value is None or not isinstance(value, dict):
+        return value
+    from crewai.agent.core import Agent
+
+    return Agent.model_validate(value, context=getattr(info, "context", None))
+
+
+def _serialize_llm_ref(value: Any) -> str | None:
+    if value is None:
+        return None
+    if isinstance(value, str):
+        return value
+    return getattr(value, "model", str(value))
+
+
 _SLUG_RE: Final[re.Pattern[str]] = re.compile(
     r"^(?:crewai-amp:)?[a-zA-Z0-9][a-zA-Z0-9_-]*(?:#[\w-]+)?$"
 )
@@ -138,6 +160,8 @@ class BaseAgent(BaseModel, ABC, metaclass=AgentMeta):
             Set private attributes.
     """
 
+    entity_type: Literal["agent"] = "agent"
+
     __hash__ = object.__hash__
     _logger: Logger = PrivateAttr(default_factory=lambda: Logger(verbose=False))
     _rpm_controller: RPMController | None = PrivateAttr(default=None)
@@ -176,9 +200,11 @@ class BaseAgent(BaseModel, ABC, metaclass=AgentMeta):
     agent_executor: InstanceOf[CrewAgentExecutorMixin] | None = Field(
         default=None, description="An instance of the CrewAgentExecutor class."
     )
-    llm: str | BaseLLM | None = Field(
-        default=None, description="Language model that will run the agent."
-    )
+    llm: Annotated[
+        str | BaseLLM | None,
+        BeforeValidator(_validate_llm_ref),
+        PlainSerializer(_serialize_llm_ref, return_type=str | None, when_used="json"),
+    ] = Field(default=None, description="Language model that will run the agent.")
     crew: Annotated[
         Crew | str | None,
         BeforeValidator(_validate_crew_ref),
@@ -197,7 +223,7 @@ class BaseAgent(BaseModel, ABC, metaclass=AgentMeta):
         description="An instance of the ToolsHandler class.",
     )
     tools_results: list[dict[str, Any]] = Field(
-        default=[], description="Results of the tools used by the agent."
+        default_factory=list, description="Results of the tools used by the agent."
     )
     max_tokens: int | None = Field(
         default=None, description="Maximum number of tokens for the agent's execution."
@@ -248,6 +274,7 @@ class BaseAgent(BaseModel, ABC, metaclass=AgentMeta):
         description="Agent Skills. Accepts paths for discovery or pre-loaded Skill objects.",
         min_length=1,
     )
+    execution_context: ExecutionContext | None = Field(default=None)
 
     @model_validator(mode="before")
     @classmethod
@@ -362,11 +389,12 @@ class BaseAgent(BaseModel, ABC, metaclass=AgentMeta):
 
     @field_validator("id", mode="before")
     @classmethod
-    def _deny_user_set_id(cls, v: UUID4 | None) -> None:
-        if v:
+    def _deny_user_set_id(cls, v: UUID4 | None, info: Any) -> UUID4 | None:
+        if v and not (info.context or {}).get("from_checkpoint"):
             raise PydanticCustomError(
                 "may_not_set_field", "This field is not to be set by the user.", {}
             )
+        return v
 
     @model_validator(mode="after")
     def set_private_attrs(self) -> Self:
@@ -423,7 +451,7 @@ class BaseAgent(BaseModel, ABC, metaclass=AgentMeta):
         pass
 
     @abstractmethod
-    def get_delegation_tools(self, agents: list[BaseAgent]) -> list[BaseTool]:
+    def get_delegation_tools(self, agents: Sequence[BaseAgent]) -> list[BaseTool]:
         """Set the task tools that init BaseAgenTools class."""
 
     @abstractmethod

lib/crewai/src/crewai/agents/tools_handler.py

@@ -3,20 +3,15 @@
 from __future__ import annotations
 
 import json
-from typing import TYPE_CHECKING, Any
 
-from pydantic import GetCoreSchemaHandler
-from pydantic_core import CoreSchema, core_schema
+from pydantic import BaseModel, Field
 
+from crewai.agents.cache.cache_handler import CacheHandler
 from crewai.tools.cache_tools.cache_tools import CacheTools
+from crewai.tools.tool_calling import InstructorToolCalling, ToolCalling
 
 
-if TYPE_CHECKING:
-    from crewai.agents.cache.cache_handler import CacheHandler
-    from crewai.tools.tool_calling import InstructorToolCalling, ToolCalling
-
-
-class ToolsHandler:
+class ToolsHandler(BaseModel):
     """Callback handler for tool usage.
 
     Attributes:
@@ -24,14 +19,8 @@ class ToolsHandler:
         cache: Optional cache handler for storing tool outputs.
     """
 
-    def __init__(self, cache: CacheHandler | None = None) -> None:
-        """Initialize the callback handler.
-
-        Args:
-            cache: Optional cache handler for storing tool outputs.
-        """
-        self.cache: CacheHandler | None = cache
-        self.last_used_tool: ToolCalling | InstructorToolCalling | None = None
+    cache: CacheHandler | None = Field(default=None)
+    last_used_tool: ToolCalling | InstructorToolCalling | None = Field(default=None)
 
     def on_tool_use(
         self,
@@ -48,7 +37,6 @@ class ToolsHandler:
         """
         self.last_used_tool = calling
         if self.cache and should_cache and calling.tool_name != CacheTools().name:
-            # Convert arguments to string for cache
             input_str = ""
             if calling.arguments:
                 if isinstance(calling.arguments, dict):
@@ -61,14 +49,3 @@ class ToolsHandler:
                 input=input_str,
                 output=output,
             )
-
-    @classmethod
-    def __get_pydantic_core_schema__(
-        cls, _source_type: Any, _handler: GetCoreSchemaHandler
-    ) -> CoreSchema:
-        """Generate Pydantic core schema for BaseClient Protocol.
-
-        This allows the Protocol to be used in Pydantic models without
-        requiring arbitrary_types_allowed=True.
-        """
-        return core_schema.any_schema()

lib/crewai/src/crewai/cli/cli.py

@@ -27,7 +27,7 @@ from crewai.cli.tools.main import ToolCommand
 from crewai.cli.train_crew import train_crew
 from crewai.cli.triggers.main import TriggersCommand
 from crewai.cli.update_crew import update_crew
-from crewai.cli.utils import build_env_with_tool_repository_credentials, read_toml
+from crewai.cli.utils import build_env_with_all_tool_credentials, read_toml
 from crewai.memory.storage.kickoff_task_outputs_storage import (
     KickoffTaskOutputsSQLiteStorage,
 )
@@ -48,24 +48,18 @@ def crewai() -> None:
 @click.argument("uv_args", nargs=-1, type=click.UNPROCESSED)
 def uv(uv_args: tuple[str, ...]) -> None:
     """A wrapper around uv commands that adds custom tool authentication through env vars."""
-    env = os.environ.copy()
     try:
-        pyproject_data = read_toml()
-        sources = pyproject_data.get("tool", {}).get("uv", {}).get("sources", {})
-
-        for source_config in sources.values():
-            if isinstance(source_config, dict):
-                index = source_config.get("index")
-                if index:
-                    index_env = build_env_with_tool_repository_credentials(index)
-                    env.update(index_env)
-    except (FileNotFoundError, KeyError) as e:
+        # Verify pyproject.toml exists first
+        read_toml()
+    except FileNotFoundError as e:
         raise SystemExit(
             "Error. A valid pyproject.toml file is required. Check that a valid pyproject.toml file exists in the current directory."
         ) from e
     except Exception as e:
         raise SystemExit(f"Error: {e}") from e
 
+    env = build_env_with_all_tool_credentials()
+
     try:
         subprocess.run(  # noqa: S603
             ["uv", *uv_args],  # noqa: S607

lib/crewai/src/crewai/cli/install_crew.py

@@ -2,6 +2,8 @@ import subprocess
 
 import click
 
+from crewai.cli.utils import build_env_with_all_tool_credentials
+
 
 # Be mindful about changing this.
 # on some environments we don't use this command but instead uv sync directly
@@ -13,7 +15,14 @@ def install_crew(proxy_options: list[str]) -> None:
     """
     try:
         command = ["uv", "sync", *proxy_options]
-        subprocess.run(command, check=True, capture_output=False, text=True)  # noqa: S603
+
+        # Inject tool repository credentials so uv can authenticate
+        # against private package indexes (e.g. crewai tool repository).
+        # Without this, `uv sync` fails with 401 Unauthorized when the
+        # project depends on tools from a private index.
+        env = build_env_with_all_tool_credentials()
+
+        subprocess.run(command, check=True, capture_output=False, text=True, env=env)  # noqa: S603
 
     except subprocess.CalledProcessError as e:
         click.echo(f"An error occurred while running the crew: {e}", err=True)

lib/crewai/src/crewai/cli/run_crew.py

@@ -1,11 +1,10 @@
 from enum import Enum
-import os
 import subprocess
 
 import click
 from packaging import version
 
-from crewai.cli.utils import build_env_with_tool_repository_credentials, read_toml
+from crewai.cli.utils import build_env_with_all_tool_credentials, read_toml
 from crewai.cli.version import get_crewai_version
 
 
@@ -56,19 +55,7 @@ def execute_command(crew_type: CrewType) -> None:
     """
     command = ["uv", "run", "kickoff" if crew_type == CrewType.FLOW else "run_crew"]
 
-    env = os.environ.copy()
-    try:
-        pyproject_data = read_toml()
-        sources = pyproject_data.get("tool", {}).get("uv", {}).get("sources", {})
-
-        for source_config in sources.values():
-            if isinstance(source_config, dict):
-                index = source_config.get("index")
-                if index:
-                    index_env = build_env_with_tool_repository_credentials(index)
-                    env.update(index_env)
-    except Exception:  # noqa: S110
-        pass
+    env = build_env_with_all_tool_credentials()
 
     try:
         subprocess.run(command, capture_output=False, text=True, check=True, env=env)  # noqa: S603

lib/crewai/src/crewai/cli/templates/crew/pyproject.toml

@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<3.14"
 dependencies = [
-    "crewai[tools]==1.13.0a7"
+    "crewai[tools]==1.13.0"
 ]
 
 [project.scripts]

lib/crewai/src/crewai/cli/templates/flow/pyproject.toml

@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<3.14"
 dependencies = [
-    "crewai[tools]==1.13.0a7"
+    "crewai[tools]==1.13.0"
 ]
 
 [project.scripts]

lib/crewai/src/crewai/cli/templates/tool/pyproject.toml

@@ -5,7 +5,7 @@ description = "Power up your crews with {{folder_name}}"
 readme = "README.md"
 requires-python = ">=3.10,<3.14"
 dependencies = [
-    "crewai[tools]==1.13.0a7"
+    "crewai[tools]==1.13.0"
 ]
 
 [tool.crewai]

lib/crewai/src/crewai/cli/tools/main.py

@@ -21,6 +21,7 @@ from crewai.cli.utils import (
     get_project_description,
     get_project_name,
     get_project_version,
+    read_toml,
     tree_copy,
     tree_find_and_replace,
 )
@@ -116,11 +117,26 @@ class ToolCommand(BaseCommand, PlusAPIMixin):
         self._print_tools_preview(tools_metadata)
         self._print_current_organization()
 
+        build_env = os.environ.copy()
+        try:
+            pyproject_data = read_toml()
+            sources = pyproject_data.get("tool", {}).get("uv", {}).get("sources", {})
+
+            for source_config in sources.values():
+                if isinstance(source_config, dict):
+                    index = source_config.get("index")
+                    if index:
+                        index_env = build_env_with_tool_repository_credentials(index)
+                        build_env.update(index_env)
+        except Exception:  # noqa: S110
+            pass
+
         with tempfile.TemporaryDirectory() as temp_build_dir:
             subprocess.run(  # noqa: S603
                 ["uv", "build", "--sdist", "--out-dir", temp_build_dir],  # noqa: S607
                 check=True,
                 capture_output=False,
+                env=build_env,
             )
 
             tarball_filename = next(

lib/crewai/src/crewai/cli/utils.py

@@ -484,8 +484,12 @@ def get_flows(flow_path: str = "main.py") -> list[Flow[Any]]:
             if flow_instances:
                 break
 
-    except Exception:  # noqa: S110
-        pass
+    except Exception as e:
+        import logging
+
+        logging.getLogger(__name__).debug(
+            f"Could not load tool repository credentials: {e}"
+        )
 
     return flow_instances
 
@@ -549,6 +553,31 @@ def build_env_with_tool_repository_credentials(
     return env
 
 
+def build_env_with_all_tool_credentials() -> dict[str, Any]:
+    """
+    Build environment dict with credentials for all tool repository indexes
+    found in pyproject.toml's [tool.uv.sources] section.
+
+    Returns:
+        dict: Environment variables with credentials for all private indexes.
+    """
+    env = os.environ.copy()
+    try:
+        pyproject_data = read_toml()
+        sources = pyproject_data.get("tool", {}).get("uv", {}).get("sources", {})
+
+        for source_config in sources.values():
+            if isinstance(source_config, dict):
+                index = source_config.get("index")
+                if index:
+                    index_env = build_env_with_tool_repository_credentials(index)
+                    env.update(index_env)
+    except Exception:  # noqa: S110
+        pass
+
+    return env
+
+
 @contextmanager
 def _load_module_from_file(
     init_file: Path, module_name: str | None = None

lib/crewai/src/crewai/context.py

@@ -4,6 +4,23 @@ import contextvars
 import os
 from typing import Any
 
+from pydantic import BaseModel, Field
+
+from crewai.events.base_events import (
+    get_emission_sequence,
+    set_emission_counter,
+)
+from crewai.events.event_context import (
+    _event_id_stack,
+    _last_event_id,
+    _triggering_event_id,
+)
+from crewai.flow.flow_context import (
+    current_flow_id,
+    current_flow_method_name,
+    current_flow_request_id,
+)
+
 
 _platform_integration_token: contextvars.ContextVar[str | None] = (
     contextvars.ContextVar("platform_integration_token", default=None)
@@ -63,3 +80,53 @@ def reset_current_task_id(token: contextvars.Token[str | None]) -> None:
 def get_current_task_id() -> str | None:
     """Get the current task ID from the context."""
     return _current_task_id.get()
+
+
+class ExecutionContext(BaseModel):
+    """Snapshot of ContextVar execution state."""
+
+    current_task_id: str | None = Field(default=None)
+    flow_request_id: str | None = Field(default=None)
+    flow_id: str | None = Field(default=None)
+    flow_method_name: str = Field(default="unknown")
+
+    event_id_stack: tuple[tuple[str, str], ...] = Field(default=())
+    last_event_id: str | None = Field(default=None)
+    triggering_event_id: str | None = Field(default=None)
+    emission_sequence: int = Field(default=0)
+
+    feedback_callback_info: dict[str, Any] | None = Field(default=None)
+    platform_token: str | None = Field(default=None)
+
+
+def capture_execution_context(
+    feedback_callback_info: dict[str, Any] | None = None,
+) -> ExecutionContext:
+    """Read current ContextVars into an ExecutionContext."""
+    return ExecutionContext(
+        current_task_id=_current_task_id.get(),
+        flow_request_id=current_flow_request_id.get(),
+        flow_id=current_flow_id.get(),
+        flow_method_name=current_flow_method_name.get(),
+        event_id_stack=_event_id_stack.get(),
+        last_event_id=_last_event_id.get(),
+        triggering_event_id=_triggering_event_id.get(),
+        emission_sequence=get_emission_sequence(),
+        feedback_callback_info=feedback_callback_info,
+        platform_token=_platform_integration_token.get(),
+    )
+
+
+def apply_execution_context(ctx: ExecutionContext) -> None:
+    """Write an ExecutionContext back into the ContextVars."""
+    _current_task_id.set(ctx.current_task_id)
+    current_flow_request_id.set(ctx.flow_request_id)
+    current_flow_id.set(ctx.flow_id)
+    current_flow_method_name.set(ctx.flow_method_name)
+
+    _event_id_stack.set(ctx.event_id_stack)
+    _last_event_id.set(ctx.last_event_id)
+    _triggering_event_id.set(ctx.triggering_event_id)
+    set_emission_counter(ctx.emission_sequence)
+
+    _platform_integration_token.set(ctx.platform_token)

lib/crewai/src/crewai/crew.py

@@ -1,7 +1,7 @@
 from __future__ import annotations
 
 import asyncio
-from collections.abc import Callable
+from collections.abc import Callable, Sequence
 from concurrent.futures import Future
 from copy import copy as shallow_copy
 from hashlib import md5
@@ -10,7 +10,9 @@ from pathlib import Path
 import re
 from typing import (
     TYPE_CHECKING,
+    Annotated,
     Any,
+    Literal,
     cast,
 )
 import uuid
@@ -21,12 +23,14 @@ from opentelemetry.context import attach, detach
 from pydantic import (
     UUID4,
     BaseModel,
+    BeforeValidator,
     Field,
     Json,
     PrivateAttr,
     field_validator,
     model_validator,
 )
+from pydantic.functional_serializers import PlainSerializer
 from pydantic_core import PydanticCustomError
 from rich.console import Console
 from rich.panel import Panel
@@ -37,6 +41,8 @@ if TYPE_CHECKING:
     from crewai_files import FileInput
     from opentelemetry.trace import Span
 
+    from crewai.context import ExecutionContext
+
 try:
     from crewai_files import get_supported_content_types
 
@@ -49,7 +55,12 @@ except ImportError:
 
 
 from crewai.agent import Agent
-from crewai.agents.agent_builder.base_agent import BaseAgent
+from crewai.agents.agent_builder.base_agent import (
+    BaseAgent,
+    _resolve_agent,
+    _serialize_llm_ref,
+    _validate_llm_ref,
+)
 from crewai.agents.cache.cache_handler import CacheHandler
 from crewai.crews.crew_output import CrewOutput
 from crewai.crews.utils import (
@@ -132,6 +143,12 @@ from crewai.utilities.training_handler import CrewTrainingHandler
 warnings.filterwarnings("ignore", category=SyntaxWarning, module="pysbd")
 
 
+def _resolve_agents(value: Any, info: Any) -> Any:
+    if not isinstance(value, list):
+        return value
+    return [_resolve_agent(a, info) for a in value]
+
+
 class Crew(FlowTrackable, BaseModel):
     """
     Represents a group of agents, defining how they should collaborate and the
@@ -170,6 +187,8 @@ class Crew(FlowTrackable, BaseModel):
             fingerprinting.
     """
 
+    entity_type: Literal["crew"] = "crew"
+
     __hash__ = object.__hash__
     _execution_span: Span | None = PrivateAttr()
     _rpm_controller: RPMController = PrivateAttr()
@@ -191,7 +210,10 @@ class Crew(FlowTrackable, BaseModel):
     name: str | None = Field(default="crew")
     cache: bool = Field(default=True)
     tasks: list[Task] = Field(default_factory=list)
-    agents: list[BaseAgent] = Field(default_factory=list)
+    agents: Annotated[
+        list[BaseAgent],
+        BeforeValidator(_resolve_agents),
+    ] = Field(default_factory=list)
     process: Process = Field(default=Process.sequential)
     verbose: bool = Field(default=False)
     memory: bool | Memory | MemoryScope | MemorySlice | None = Field(
@@ -209,15 +231,20 @@ class Crew(FlowTrackable, BaseModel):
         default=None,
         description="Metrics for the LLM usage during all tasks execution.",
     )
-    manager_llm: str | BaseLLM | None = Field(
-        description="Language model that will run the agent.", default=None
-    )
-    manager_agent: BaseAgent | None = Field(
-        description="Custom agent that will be used as manager.", default=None
-    )
-    function_calling_llm: str | LLM | None = Field(
-        description="Language model that will run the agent.", default=None
-    )
+    manager_llm: Annotated[
+        str | BaseLLM | None,
+        BeforeValidator(_validate_llm_ref),
+        PlainSerializer(_serialize_llm_ref, return_type=str | None, when_used="json"),
+    ] = Field(description="Language model that will run the agent.", default=None)
+    manager_agent: Annotated[
+        BaseAgent | None,
+        BeforeValidator(_resolve_agent),
+    ] = Field(description="Custom agent that will be used as manager.", default=None)
+    function_calling_llm: Annotated[
+        str | LLM | None,
+        BeforeValidator(_validate_llm_ref),
+        PlainSerializer(_serialize_llm_ref, return_type=str | None, when_used="json"),
+    ] = Field(description="Language model that will run the agent.", default=None)
     config: Json[dict[str, Any]] | dict[str, Any] | None = Field(default=None)
     id: UUID4 = Field(default_factory=uuid.uuid4, frozen=True)
     share_crew: bool | None = Field(default=False)
@@ -266,7 +293,11 @@ class Crew(FlowTrackable, BaseModel):
         default=False,
         description="Plan the crew execution and add the plan to the crew.",
     )
-    planning_llm: str | BaseLLM | None = Field(
+    planning_llm: Annotated[
+        str | BaseLLM | None,
+        BeforeValidator(_validate_llm_ref),
+        PlainSerializer(_serialize_llm_ref, return_type=str | None, when_used="json"),
+    ] = Field(
         default=None,
         description=(
             "Language model that will run the AgentPlanner if planning is True."
@@ -287,7 +318,11 @@ class Crew(FlowTrackable, BaseModel):
             "knowledge object."
         ),
     )
-    chat_llm: str | BaseLLM | None = Field(
+    chat_llm: Annotated[
+        str | BaseLLM | None,
+        BeforeValidator(_validate_llm_ref),
+        PlainSerializer(_serialize_llm_ref, return_type=str | None, when_used="json"),
+    ] = Field(
         default=None,
         description="LLM used to handle chatting with the crew.",
     )
@@ -313,14 +348,20 @@ class Crew(FlowTrackable, BaseModel):
         description="Whether to enable tracing for the crew. True=always enable, False=always disable, None=check environment/user settings.",
     )
 
+    execution_context: ExecutionContext | None = Field(default=None)
+    checkpoint_inputs: dict[str, Any] | None = Field(default=None)
+    checkpoint_train: bool | None = Field(default=None)
+    checkpoint_kickoff_event_id: str | None = Field(default=None)
+
     @field_validator("id", mode="before")
     @classmethod
-    def _deny_user_set_id(cls, v: UUID4 | None) -> None:
+    def _deny_user_set_id(cls, v: UUID4 | None, info: Any) -> UUID4 | None:
         """Prevent manual setting of the 'id' field by users."""
-        if v:
+        if v and not (info.context or {}).get("from_checkpoint"):
             raise PydanticCustomError(
                 "may_not_set_field", "The 'id' field cannot be set by the user.", {}
             )
+        return v
 
     @field_validator("config", mode="before")
     @classmethod
@@ -1388,7 +1429,7 @@ class Crew(FlowTrackable, BaseModel):
         self,
         tools: list[BaseTool],
         task_agent: BaseAgent,
-        agents: list[BaseAgent],
+        agents: Sequence[BaseAgent],
     ) -> list[BaseTool]:
         if hasattr(task_agent, "get_delegation_tools"):
             delegation_tools = task_agent.get_delegation_tools(agents)

lib/crewai/src/crewai/crews/crew_output.py

@@ -21,7 +21,7 @@ class CrewOutput(BaseModel):
         description="JSON dict output of Crew", default=None
     )
     tasks_output: list[TaskOutput] = Field(
-        description="Output of each task", default=[]
+        description="Output of each task", default_factory=list
     )
     token_usage: UsageMetrics = Field(
         description="Processed token summary", default_factory=UsageMetrics

lib/crewai/src/crewai/events/event_listener.py

@@ -78,9 +78,15 @@ from crewai.events.types.mcp_events import (
     MCPConnectionCompletedEvent,
     MCPConnectionFailedEvent,
     MCPConnectionStartedEvent,
+    MCPToolExecutionCompletedEvent,
     MCPToolExecutionFailedEvent,
     MCPToolExecutionStartedEvent,
 )
+from crewai.events.types.memory_events import (
+    MemoryQueryCompletedEvent,
+    MemoryRetrievalCompletedEvent,
+    MemorySaveCompletedEvent,
+)
 from crewai.events.types.observation_events import (
     GoalAchievedEarlyEvent,
     PlanRefinementEvent,
@@ -94,6 +100,12 @@ from crewai.events.types.reasoning_events import (
     AgentReasoningFailedEvent,
     AgentReasoningStartedEvent,
 )
+from crewai.events.types.skill_events import (
+    SkillActivatedEvent,
+    SkillDiscoveryCompletedEvent,
+    SkillLoadFailedEvent,
+    SkillLoadedEvent,
+)
 from crewai.events.types.task_events import (
     TaskCompletedEvent,
     TaskFailedEvent,
@@ -478,6 +490,7 @@ class EventListener(BaseEventListener):
             self.formatter.handle_guardrail_completed(
                 event.success, event.error, event.retry_count
             )
+            self._telemetry.feature_usage_span("guardrail:execution")
 
         @crewai_event_bus.on(CrewTestStartedEvent)
         def on_crew_test_started(source: Any, event: CrewTestStartedEvent) -> None:
@@ -559,6 +572,7 @@ class EventListener(BaseEventListener):
                 event.plan,
                 event.ready,
             )
+            self._telemetry.feature_usage_span("planning:creation")
 
         @crewai_event_bus.on(AgentReasoningFailedEvent)
         def on_agent_reasoning_failed(_: Any, event: AgentReasoningFailedEvent) -> None:
@@ -616,6 +630,7 @@ class EventListener(BaseEventListener):
                 event.replan_count,
                 event.completed_steps_preserved,
             )
+            self._telemetry.feature_usage_span("planning:replan")
 
         @crewai_event_bus.on(GoalAchievedEarlyEvent)
         def on_goal_achieved_early(_: Any, event: GoalAchievedEarlyEvent) -> None:
@@ -623,6 +638,25 @@ class EventListener(BaseEventListener):
                 event.steps_completed,
                 event.steps_remaining,
             )
+            self._telemetry.feature_usage_span("planning:goal_achieved_early")
+
+        # ----------- SKILL EVENTS -----------
+
+        @crewai_event_bus.on(SkillDiscoveryCompletedEvent)
+        def on_skill_discovery(_: Any, event: SkillDiscoveryCompletedEvent) -> None:
+            self._telemetry.feature_usage_span("skill:discovery")
+
+        @crewai_event_bus.on(SkillLoadedEvent)
+        def on_skill_loaded(_: Any, event: SkillLoadedEvent) -> None:
+            self._telemetry.feature_usage_span("skill:loaded")
+
+        @crewai_event_bus.on(SkillLoadFailedEvent)
+        def on_skill_load_failed(_: Any, event: SkillLoadFailedEvent) -> None:
+            self._telemetry.feature_usage_span("skill:load_failed")
+
+        @crewai_event_bus.on(SkillActivatedEvent)
+        def on_skill_activated(_: Any, event: SkillActivatedEvent) -> None:
+            self._telemetry.feature_usage_span("skill:activated")
 
         # ----------- AGENT LOGGING EVENTS -----------
 
@@ -662,6 +696,7 @@ class EventListener(BaseEventListener):
                 event.error,
                 event.is_multiturn,
             )
+            self._telemetry.feature_usage_span("a2a:delegation")
 
         @crewai_event_bus.on(A2AConversationStartedEvent)
         def on_a2a_conversation_started(
@@ -703,6 +738,7 @@ class EventListener(BaseEventListener):
                 event.error,
                 event.total_turns,
             )
+            self._telemetry.feature_usage_span("a2a:conversation")
 
         @crewai_event_bus.on(A2APollingStartedEvent)
         def on_a2a_polling_started(_: Any, event: A2APollingStartedEvent) -> None:
@@ -744,6 +780,7 @@ class EventListener(BaseEventListener):
                 event.connection_duration_ms,
                 event.is_reconnect,
             )
+            self._telemetry.feature_usage_span("mcp:connection")
 
         @crewai_event_bus.on(MCPConnectionFailedEvent)
         def on_mcp_connection_failed(_: Any, event: MCPConnectionFailedEvent) -> None:
@@ -754,6 +791,7 @@ class EventListener(BaseEventListener):
                 event.error,
                 event.error_type,
             )
+            self._telemetry.feature_usage_span("mcp:connection_failed")
 
         @crewai_event_bus.on(MCPConfigFetchFailedEvent)
         def on_mcp_config_fetch_failed(
@@ -764,6 +802,7 @@ class EventListener(BaseEventListener):
                 event.error,
                 event.error_type,
             )
+            self._telemetry.feature_usage_span("mcp:config_fetch_failed")
 
         @crewai_event_bus.on(MCPToolExecutionStartedEvent)
         def on_mcp_tool_execution_started(
@@ -775,6 +814,12 @@ class EventListener(BaseEventListener):
                 event.tool_args,
             )
 
+        @crewai_event_bus.on(MCPToolExecutionCompletedEvent)
+        def on_mcp_tool_execution_completed(
+            _: Any, event: MCPToolExecutionCompletedEvent
+        ) -> None:
+            self._telemetry.feature_usage_span("mcp:tool_execution")
+
         @crewai_event_bus.on(MCPToolExecutionFailedEvent)
         def on_mcp_tool_execution_failed(
             _: Any, event: MCPToolExecutionFailedEvent
@@ -786,6 +831,45 @@ class EventListener(BaseEventListener):
                 event.error,
                 event.error_type,
             )
+            self._telemetry.feature_usage_span("mcp:tool_execution_failed")
+
+        # ----------- MEMORY TELEMETRY -----------
+
+        @crewai_event_bus.on(MemorySaveCompletedEvent)
+        def on_memory_save_completed(_: Any, event: MemorySaveCompletedEvent) -> None:
+            self._telemetry.feature_usage_span("memory:save")
+
+        @crewai_event_bus.on(MemoryQueryCompletedEvent)
+        def on_memory_query_completed(_: Any, event: MemoryQueryCompletedEvent) -> None:
+            self._telemetry.feature_usage_span("memory:query")
+
+        @crewai_event_bus.on(MemoryRetrievalCompletedEvent)
+        def on_memory_retrieval_completed_telemetry(
+            _: Any, event: MemoryRetrievalCompletedEvent
+        ) -> None:
+            self._telemetry.feature_usage_span("memory:retrieval")
+
+        @crewai_event_bus.on(CrewKickoffStartedEvent)
+        def on_crew_kickoff_hooks(_: Any, event: CrewKickoffStartedEvent) -> None:
+            from crewai.hooks.llm_hooks import (
+                get_after_llm_call_hooks,
+                get_before_llm_call_hooks,
+            )
+            from crewai.hooks.tool_hooks import (
+                get_after_tool_call_hooks,
+                get_before_tool_call_hooks,
+            )
+
+            has_hooks = any(
+                [
+                    get_before_llm_call_hooks(),
+                    get_after_llm_call_hooks(),
+                    get_before_tool_call_hooks(),
+                    get_after_tool_call_hooks(),
+                ]
+            )
+            if has_hooks:
+                self._telemetry.feature_usage_span("hooks:registered")
 
 
 event_listener = EventListener()

lib/crewai/src/crewai/execution_context.py

@@ -1,80 +0,0 @@
-"""Checkpointable execution context for the crewAI runtime.
-
-Captures the ContextVar state needed to resume execution from a checkpoint.
-Used by the RootModel (step 5) to include execution context in snapshots.
-"""
-
-from __future__ import annotations
-
-from typing import Any
-
-from pydantic import BaseModel, Field
-
-from crewai.context import (
-    _current_task_id,
-    _platform_integration_token,
-)
-from crewai.events.base_events import (
-    get_emission_sequence,
-    set_emission_counter,
-)
-from crewai.events.event_context import (
-    _event_id_stack,
-    _last_event_id,
-    _triggering_event_id,
-)
-from crewai.flow.flow_context import (
-    current_flow_id,
-    current_flow_method_name,
-    current_flow_request_id,
-)
-
-
-class ExecutionContext(BaseModel):
-    """Snapshot of ContextVar state required for checkpoint/resume."""
-
-    current_task_id: str | None = Field(default=None)
-    flow_request_id: str | None = Field(default=None)
-    flow_id: str | None = Field(default=None)
-    flow_method_name: str = Field(default="unknown")
-
-    event_id_stack: tuple[tuple[str, str], ...] = Field(default=())
-    last_event_id: str | None = Field(default=None)
-    triggering_event_id: str | None = Field(default=None)
-    emission_sequence: int = Field(default=0)
-
-    feedback_callback_info: dict[str, Any] | None = Field(default=None)
-    platform_token: str | None = Field(default=None)
-
-
-def capture_execution_context(
-    feedback_callback_info: dict[str, Any] | None = None,
-) -> ExecutionContext:
-    """Read all checkpoint-required ContextVars into an ExecutionContext."""
-    return ExecutionContext(
-        current_task_id=_current_task_id.get(),
-        flow_request_id=current_flow_request_id.get(),
-        flow_id=current_flow_id.get(),
-        flow_method_name=current_flow_method_name.get(),
-        event_id_stack=_event_id_stack.get(),
-        last_event_id=_last_event_id.get(),
-        triggering_event_id=_triggering_event_id.get(),
-        emission_sequence=get_emission_sequence(),
-        feedback_callback_info=feedback_callback_info,
-        platform_token=_platform_integration_token.get(),
-    )
-
-
-def apply_execution_context(ctx: ExecutionContext) -> None:
-    """Write an ExecutionContext back into the ContextVars."""
-    _current_task_id.set(ctx.current_task_id)
-    current_flow_request_id.set(ctx.flow_request_id)
-    current_flow_id.set(ctx.flow_id)
-    current_flow_method_name.set(ctx.flow_method_name)
-
-    _event_id_stack.set(ctx.event_id_stack)
-    _last_event_id.set(ctx.last_event_id)
-    _triggering_event_id.set(ctx.triggering_event_id)
-    set_emission_counter(ctx.emission_sequence)
-
-    _platform_integration_token.set(ctx.platform_token)

lib/crewai/src/crewai/experimental/agent_executor.py

@@ -1907,6 +1907,37 @@ class AgentExecutor(Flow[AgentExecutorState], CrewAgentExecutorMixin):
             "original_tool": original_tool,
         }
 
+    def _extract_tool_name(self, tool_call: Any) -> str:
+        """Extract tool name from various tool call formats."""
+        if hasattr(tool_call, "function"):
+            return sanitize_tool_name(tool_call.function.name)
+        if hasattr(tool_call, "function_call") and tool_call.function_call:
+            return sanitize_tool_name(tool_call.function_call.name)
+        if hasattr(tool_call, "name"):
+            return sanitize_tool_name(tool_call.name)
+        if isinstance(tool_call, dict):
+            func_info = tool_call.get("function", {})
+            return sanitize_tool_name(
+                func_info.get("name", "") or tool_call.get("name", "unknown")
+            )
+        return "unknown"
+
+    @router(execute_native_tool)
+    def check_native_todo_completion(
+        self,
+    ) -> Literal["todo_satisfied", "todo_not_satisfied"]:
+        """Check if the native tool execution satisfied the active todo.
+
+        Similar to check_todo_completion but for native tool execution path.
+        """
+        current_todo = self.state.todos.current_todo
+
+        if not current_todo:
+            return "todo_not_satisfied"
+
+        # For native tools, any tool execution satisfies the todo
+        return "todo_satisfied"
+
     @listen("initialized")
     def continue_iteration(self) -> Literal["check_iteration"]:
         """Bridge listener that connects iteration loop back to iteration check."""

lib/crewai/src/crewai/flow/flow.py

@@ -25,6 +25,7 @@ import logging
 import threading
 from typing import (
     TYPE_CHECKING,
+    Annotated,
     Any,
     ClassVar,
     Generic,
@@ -41,9 +42,11 @@ from opentelemetry import baggage
 from opentelemetry.context import attach, detach
 from pydantic import (
     BaseModel,
+    BeforeValidator,
     ConfigDict,
     Field,
     PrivateAttr,
+    SerializeAsAny,
     ValidationError,
 )
 from pydantic._internal._model_construction import ModelMetaclass
@@ -115,6 +118,7 @@ from crewai.memory.unified_memory import Memory
 if TYPE_CHECKING:
     from crewai_files import FileInput
 
+    from crewai.context import ExecutionContext
     from crewai.flow.async_feedback.types import PendingFeedbackContext
     from crewai.llms.base_llm import BaseLLM
 
@@ -134,6 +138,19 @@ from crewai.utilities.streaming import (
 logger = logging.getLogger(__name__)
 
 
+def _resolve_persistence(value: Any) -> Any:
+    if value is None or isinstance(value, FlowPersistence):
+        return value
+    if isinstance(value, dict):
+        from crewai.flow.persistence.base import _persistence_registry
+
+        type_name = value.get("persistence_type", "SQLiteFlowPersistence")
+        cls = _persistence_registry.get(type_name)
+        if cls is not None:
+            return cls.model_validate(value)
+    return value
+
+
 class FlowState(BaseModel):
     """Base model for all flow states, ensuring each state has a unique ID."""
 
@@ -883,6 +900,8 @@ class Flow(BaseModel, Generic[T], metaclass=FlowMeta):
     _routers: ClassVar[set[FlowMethodName]] = set()
     _router_paths: ClassVar[dict[FlowMethodName, list[FlowMethodName]]] = {}
 
+    entity_type: Literal["flow"] = "flow"
+
     initial_state: Any = Field(default=None)
     name: str | None = Field(default=None)
     tracing: bool | None = Field(default=None)
@@ -893,8 +912,17 @@ class Flow(BaseModel, Generic[T], metaclass=FlowMeta):
     human_feedback_history: list[HumanFeedbackResult] = Field(default_factory=list)
     last_human_feedback: HumanFeedbackResult | None = Field(default=None)
 
-    persistence: Any = Field(default=None, exclude=True)
-    max_method_calls: int = Field(default=100, exclude=True)
+    persistence: Annotated[
+        SerializeAsAny[FlowPersistence] | Any,
+        BeforeValidator(lambda v, _: _resolve_persistence(v)),
+    ] = Field(default=None)
+    max_method_calls: int = Field(default=100)
+
+    execution_context: ExecutionContext | None = Field(default=None)
+    checkpoint_completed_methods: set[str] | None = Field(default=None)
+    checkpoint_method_outputs: list[Any] | None = Field(default=None)
+    checkpoint_method_counts: dict[str, int] | None = Field(default=None)
+    checkpoint_state: dict[str, Any] | None = Field(default=None)
 
     _methods: dict[FlowMethodName, FlowMethod[Any, Any]] = PrivateAttr(
         default_factory=dict

lib/crewai/src/crewai/flow/persistence/base.py

@@ -5,14 +5,17 @@ from __future__ import annotations
 from abc import ABC, abstractmethod
 from typing import TYPE_CHECKING, Any
 
-from pydantic import BaseModel
+from pydantic import BaseModel, Field
 
 
 if TYPE_CHECKING:
     from crewai.flow.async_feedback.types import PendingFeedbackContext
 
 
-class FlowPersistence(ABC):
+_persistence_registry: dict[str, type[FlowPersistence]] = {}
+
+
+class FlowPersistence(BaseModel, ABC):
     """Abstract base class for flow state persistence.
 
     This class defines the interface that all persistence implementations must follow.
@@ -24,6 +27,13 @@ class FlowPersistence(ABC):
     - clear_pending_feedback(): Clears pending feedback after resume
     """
 
+    persistence_type: str = Field(default="base")
+
+    def __init_subclass__(cls, **kwargs: Any) -> None:
+        super().__init_subclass__(**kwargs)
+        if not getattr(cls, "__abstractmethods__", set()):
+            _persistence_registry[cls.__name__] = cls
+
     @abstractmethod
     def init_db(self) -> None:
         """Initialize the persistence backend.
@@ -95,7 +105,7 @@ class FlowPersistence(ABC):
         """
         return None
 
-    def clear_pending_feedback(self, flow_uuid: str) -> None:  # noqa: B027
+    def clear_pending_feedback(self, flow_uuid: str) -> None:
         """Clear the pending feedback marker after successful resume.
 
         This is called after feedback is received and the flow resumes.

lib/crewai/src/crewai/flow/persistence/sqlite.py

@@ -9,7 +9,8 @@ from pathlib import Path
 import sqlite3
 from typing import TYPE_CHECKING, Any
 
-from pydantic import BaseModel
+from pydantic import BaseModel, Field, PrivateAttr, model_validator
+from typing_extensions import Self
 
 from crewai.flow.persistence.base import FlowPersistence
 from crewai.utilities.lock_store import lock as store_lock
@@ -50,26 +51,22 @@ class SQLiteFlowPersistence(FlowPersistence):
         ```
     """
 
-    def __init__(self, db_path: str | None = None) -> None:
-        """Initialize SQLite persistence.
+    persistence_type: str = Field(default="SQLiteFlowPersistence")
+    db_path: str = Field(
+        default_factory=lambda: str(Path(db_storage_path()) / "flow_states.db")
+    )
+    _lock_name: str = PrivateAttr()
 
-        Args:
-            db_path: Path to the SQLite database file. If not provided, uses
-                    db_storage_path() from utilities.paths.
+    def __init__(self, db_path: str | None = None, /, **kwargs: Any) -> None:
+        if db_path is not None:
+            kwargs["db_path"] = db_path
+        super().__init__(**kwargs)
 
-        Raises:
-            ValueError: If db_path is invalid
-        """
-
-        # Get path from argument or default location
-        path = db_path or str(Path(db_storage_path()) / "flow_states.db")
-
-        if not path:
-            raise ValueError("Database path must be provided")
-
-        self.db_path = path  # Now mypy knows this is str
+    @model_validator(mode="after")
+    def _setup(self) -> Self:
         self._lock_name = f"sqlite:{os.path.realpath(self.db_path)}"
         self.init_db()
+        return self
 
     def init_db(self) -> None:
         """Create the necessary tables if they don't exist."""

lib/crewai/src/crewai/lite_agent_output.py

@@ -40,7 +40,9 @@ class LiteAgentOutput(BaseModel):
     usage_metrics: dict[str, Any] | None = Field(
         description="Token usage metrics for this execution", default=None
     )
-    messages: list[LLMMessage] = Field(description="Messages of the agent", default=[])
+    messages: list[LLMMessage] = Field(
+        description="Messages of the agent", default_factory=list
+    )
 
     plan: str | None = Field(
         default=None, description="The execution plan that was generated, if any"

lib/crewai/src/crewai/memory/memory_scope.py

@@ -32,6 +32,10 @@ class MemoryScope(BaseModel):
         """Extract memory dependency and normalize root path before validation."""
         if isinstance(data, MemoryScope):
             return data
+        if not isinstance(data, dict):
+            raise ValueError(f"Expected dict or MemoryScope, got {type(data).__name__}")
+        if "memory" not in data:
+            raise ValueError("MemoryScope requires a 'memory' key")
         memory = data.pop("memory")
         instance: MemoryScope = handler(data)
         instance._memory = memory
@@ -199,6 +203,10 @@ class MemorySlice(BaseModel):
         """Extract memory dependency and normalize scopes before validation."""
         if isinstance(data, MemorySlice):
             return data
+        if not isinstance(data, dict):
+            raise ValueError(f"Expected dict or MemorySlice, got {type(data).__name__}")
+        if "memory" not in data:
+            raise ValueError("MemorySlice requires a 'memory' key")
         memory = data.pop("memory")
         data["scopes"] = [s.rstrip("/") or "/" for s in data.get("scopes", [])]
         instance: MemorySlice = handler(data)

lib/crewai/src/crewai/runtime_state.py

@@ -0,0 +1,18 @@
+"""Unified runtime state for crewAI.
+
+``RuntimeState`` is a ``RootModel`` whose ``model_dump_json()`` produces a
+complete, self-contained snapshot of every active entity in the program.
+
+The ``Entity`` type alias and ``RuntimeState`` model are built at import time
+in ``crewai/__init__.py`` after all forward references are resolved.
+"""
+
+from typing import Any
+
+
+def _entity_discriminator(v: dict[str, Any] | object) -> str:
+    if isinstance(v, dict):
+        raw = v.get("entity_type", "agent")
+    else:
+        raw = getattr(v, "entity_type", "agent")
+    return str(raw)

lib/crewai/src/crewai/task.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 import asyncio
+from collections.abc import Sequence
 from concurrent.futures import Future
 import contextvars
 from copy import copy as shallow_copy
@@ -12,6 +13,7 @@ import logging
 from pathlib import Path
 import threading
 from typing import (
+    Annotated,
     Any,
     ClassVar,
     cast,
@@ -24,6 +26,7 @@ import warnings
 from pydantic import (
     UUID4,
     BaseModel,
+    BeforeValidator,
     Field,
     PrivateAttr,
     field_validator,
@@ -32,7 +35,7 @@ from pydantic import (
 from pydantic_core import PydanticCustomError
 from typing_extensions import Self
 
-from crewai.agents.agent_builder.base_agent import BaseAgent
+from crewai.agents.agent_builder.base_agent import BaseAgent, _resolve_agent
 from crewai.context import reset_current_task_id, set_current_task_id
 from crewai.core.providers.content_processor import process_content
 from crewai.events.event_bus import crewai_event_bus
@@ -129,9 +132,10 @@ class Task(BaseModel):
     callback: SerializableCallable | None = Field(
         description="Callback to be executed after the task is completed.", default=None
     )
-    agent: BaseAgent | None = Field(
-        description="Agent responsible for execution the task.", default=None
-    )
+    agent: Annotated[
+        BaseAgent | None,
+        BeforeValidator(_resolve_agent),
+    ] = Field(description="Agent responsible for execution the task.", default=None)
     context: list[Task] | None | _NotSpecified = Field(
         description="Other tasks that will have their output used as context for this task.",
         default=NOT_SPECIFIED,
@@ -392,11 +396,12 @@ class Task(BaseModel):
 
     @field_validator("id", mode="before")
     @classmethod
-    def _deny_user_set_id(cls, v: UUID4 | None) -> None:
-        if v:
+    def _deny_user_set_id(cls, v: UUID4 | None, info: Any) -> UUID4 | None:
+        if v and not (info.context or {}).get("from_checkpoint"):
             raise PydanticCustomError(
                 "may_not_set_field", "This field is not to be set by the user.", {}
             )
+        return v
 
     @field_validator("input_files", mode="before")
     @classmethod
@@ -997,7 +1002,7 @@ Follow these guidelines:
         self.delegations += 1
 
     def copy(  # type: ignore
-        self, agents: list[BaseAgent], task_mapping: dict[str, Task]
+        self, agents: Sequence[BaseAgent], task_mapping: dict[str, Task]
     ) -> Task:
         """Creates a deep copy of the Task while preserving its original class type.
 

lib/crewai/src/crewai/tasks/conditional_task.py

@@ -8,6 +8,7 @@ from pydantic import Field
 from crewai.task import Task
 from crewai.tasks.output_format import OutputFormat
 from crewai.tasks.task_output import TaskOutput
+from crewai.types.callback import SerializableCallable
 
 
 class ConditionalTask(Task):
@@ -24,7 +25,7 @@ class ConditionalTask(Task):
         - Cannot be the first task since it needs context from the previous task
     """
 
-    condition: Callable[[TaskOutput], bool] | None = Field(
+    condition: SerializableCallable | None = Field(
         default=None,
         description="Function that determines whether the task should be executed based on previous task output.",
     )
@@ -51,7 +52,7 @@ class ConditionalTask(Task):
         """
         if self.condition is None:
             raise ValueError("No condition function set for conditional task")
-        return self.condition(context)
+        return bool(self.condition(context))
 
     def get_skipped_task_output(self) -> TaskOutput:
         """Generate a TaskOutput for when the conditional task is skipped.

lib/crewai/src/crewai/tasks/task_output.py

@@ -43,7 +43,9 @@ class TaskOutput(BaseModel):
     output_format: OutputFormat = Field(
         description="Output format of the task", default=OutputFormat.RAW
     )
-    messages: list[LLMMessage] = Field(description="Messages of the task", default=[])
+    messages: list[LLMMessage] = Field(
+        description="Messages of the task", default_factory=list
+    )
 
     @model_validator(mode="after")
     def set_summary(self) -> TaskOutput:

lib/crewai/src/crewai/telemetry/telemetry.py

@@ -1040,3 +1040,20 @@ class Telemetry:
             close_span(span)
 
         self._safe_telemetry_operation(_operation)
+
+    def feature_usage_span(self, feature: str) -> None:
+        """Records that a feature was used. One span = one count.
+
+        Args:
+            feature: Feature identifier, e.g. "planning:creation",
+                     "mcp:connection", "a2a:delegation".
+        """
+
+        def _operation() -> None:
+            tracer = trace.get_tracer("crewai.telemetry")
+            span = tracer.start_span("Feature Usage")
+            self._add_attribute(span, "crewai_version", version("crewai"))
+            self._add_attribute(span, "feature", feature)
+            close_span(span)
+
+        self._safe_telemetry_operation(_operation)

lib/crewai/src/crewai/tools/agent_tools/agent_tools.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+from collections.abc import Sequence
 from typing import TYPE_CHECKING
 
 from crewai.tools.agent_tools.ask_question_tool import AskQuestionTool
@@ -16,7 +17,7 @@ if TYPE_CHECKING:
 class AgentTools:
     """Manager class for agent-related tools"""
 
-    def __init__(self, agents: list[BaseAgent], i18n: I18N | None = None) -> None:
+    def __init__(self, agents: Sequence[BaseAgent], i18n: I18N | None = None) -> None:
         self.agents = agents
         self.i18n = i18n if i18n is not None else get_i18n()
 

lib/crewai/src/crewai/tools/tool_usage.py

@@ -318,6 +318,8 @@ class ToolUsage:
                         if self.task:
                             self.task.increment_delegations(coworker)
 
+                    fingerprint_config = self._build_fingerprint_config()
+
                     if calling.arguments:
                         try:
                             acceptable_args = tool.args_schema.model_json_schema()[
@@ -328,15 +330,16 @@ class ToolUsage:
                                 for k, v in calling.arguments.items()
                                 if k in acceptable_args
                             }
-                            arguments = self._add_fingerprint_metadata(arguments)
-                            result = await tool.ainvoke(input=arguments)
+                            result = await tool.ainvoke(
+                                input=arguments, config=fingerprint_config
+                            )
                         except Exception:
                             arguments = calling.arguments
-                            arguments = self._add_fingerprint_metadata(arguments)
-                            result = await tool.ainvoke(input=arguments)
+                            result = await tool.ainvoke(
+                                input=arguments, config=fingerprint_config
+                            )
                     else:
-                        arguments = self._add_fingerprint_metadata({})
-                        result = await tool.ainvoke(input=arguments)
+                        result = await tool.ainvoke(input={}, config=fingerprint_config)
 
                     if self.tools_handler:
                         should_cache = True
@@ -550,6 +553,8 @@ class ToolUsage:
                         if self.task:
                             self.task.increment_delegations(coworker)
 
+                    fingerprint_config = self._build_fingerprint_config()
+
                     if calling.arguments:
                         try:
                             acceptable_args = tool.args_schema.model_json_schema()[
@@ -560,15 +565,16 @@ class ToolUsage:
                                 for k, v in calling.arguments.items()
                                 if k in acceptable_args
                             }
-                            arguments = self._add_fingerprint_metadata(arguments)
-                            result = tool.invoke(input=arguments)
+                            result = tool.invoke(
+                                input=arguments, config=fingerprint_config
+                            )
                         except Exception:
                             arguments = calling.arguments
-                            arguments = self._add_fingerprint_metadata(arguments)
-                            result = tool.invoke(input=arguments)
+                            result = tool.invoke(
+                                input=arguments, config=fingerprint_config
+                            )
                     else:
-                        arguments = self._add_fingerprint_metadata({})
-                        result = tool.invoke(input=arguments)
+                        result = tool.invoke(input={}, config=fingerprint_config)
 
                     if self.tools_handler:
                         should_cache = True
@@ -1008,23 +1014,16 @@ class ToolUsage:
 
         return event_data
 
-    def _add_fingerprint_metadata(self, arguments: dict[str, Any]) -> dict[str, Any]:
-        """Add fingerprint metadata to tool arguments if available.
+    def _build_fingerprint_config(self) -> dict[str, Any]:
+        """Build fingerprint metadata as a config dict for tool invocation.
 
-        Args:
-            arguments: The original tool arguments
+        Returns the fingerprint data in a config dict rather than injecting it
+        into tool arguments, so it doesn't conflict with strict tool schemas.
 
         Returns:
-            Updated arguments dictionary with fingerprint metadata
+            Config dictionary with security_context metadata.
         """
-        # Create a shallow copy to avoid modifying the original
-        arguments = arguments.copy()
-
-        # Add security metadata under a designated key
-        if "security_context" not in arguments:
-            arguments["security_context"] = {}
-
-        security_context = arguments["security_context"]
+        security_context: dict[str, Any] = {}
 
         # Add agent fingerprint if available
         if self.agent and hasattr(self.agent, "security_config"):
@@ -1048,4 +1047,4 @@ class ToolUsage:
                 except AttributeError:
                     pass
 
-        return arguments
+        return {"security_context": security_context} if security_context else {}

lib/crewai/src/crewai/utilities/constants.py

@@ -1,5 +1,7 @@
 from typing import Annotated, Final
 
+from pydantic_core import CoreSchema
+
 from crewai.utilities.printer import PrinterColor
 
 
@@ -36,6 +38,25 @@ class _NotSpecified:
     def __repr__(self) -> str:
         return "NOT_SPECIFIED"
 
+    @classmethod
+    def __get_pydantic_core_schema__(
+        cls, _source_type: object, _handler: object
+    ) -> CoreSchema:
+        from pydantic_core import core_schema
+
+        def _validate(v: object) -> _NotSpecified:
+            if isinstance(v, _NotSpecified) or v == "NOT_SPECIFIED":
+                return NOT_SPECIFIED
+            raise ValueError(f"Expected NOT_SPECIFIED sentinel, got {type(v).__name__}")
+
+        return core_schema.no_info_plain_validator_function(
+            _validate,
+            serialization=core_schema.plain_serializer_function_ser_schema(
+                lambda v: "NOT_SPECIFIED",
+                info_arg=False,
+            ),
+        )
+
 
 NOT_SPECIFIED: Final[
     Annotated[

lib/crewai/tests/agents/test_agent_executor.py

@@ -927,6 +927,30 @@ class TestNativeToolExecution:
         assert len(tool_messages) == 1
         assert tool_messages[0]["tool_call_id"] == "call_1"
 
+    def test_check_native_todo_completion_requires_current_todo(
+        self, mock_dependencies
+    ):
+        from crewai.utilities.planning_types import TodoList
+
+        executor = _build_executor(**mock_dependencies)
+
+        # No current todo → not satisfied
+        executor.state.todos = TodoList(items=[])
+        assert executor.check_native_todo_completion() == "todo_not_satisfied"
+
+        # With a current todo that has tool_to_use → satisfied
+        running = TodoItem(
+            step_number=1,
+            description="Use the expected tool",
+            tool_to_use="expected_tool",
+            status="running",
+        )
+        executor.state.todos = TodoList(items=[running])
+        assert executor.check_native_todo_completion() == "todo_satisfied"
+
+        # With a current todo without tool_to_use → still satisfied
+        running.tool_to_use = None
+        assert executor.check_native_todo_completion() == "todo_satisfied"
 
 
 class TestPlannerObserver:

lib/crewai/tests/cli/tools/test_main.py

@@ -218,6 +218,7 @@ def test_publish_when_not_in_sync_and_force(
         ["uv", "build", "--sdist", "--out-dir", unittest.mock.ANY],
         check=True,
         capture_output=False,
+        env=unittest.mock.ANY,
     )
     mock_open.assert_called_with(unittest.mock.ANY, "rb")
     mock_publish.assert_called_with(
@@ -279,6 +280,7 @@ def test_publish_success(
         ["uv", "build", "--sdist", "--out-dir", unittest.mock.ANY],
         check=True,
         capture_output=False,
+        env=unittest.mock.ANY,
     )
     mock_open.assert_called_with(unittest.mock.ANY, "rb")
     mock_publish.assert_called_with(

lib/crewai/tests/test_docs_links.py

@@ -0,0 +1,85 @@
+"""Tests to ensure documentation links are up-to-date and correct.
+
+These tests verify that outdated or broken links in documentation files
+are caught early and prevent regressions (e.g., issue #5253).
+"""
+
+import os
+import re
+
+import pytest
+
+DOCS_DIR = os.path.join(
+    os.path.dirname(__file__), "..", "..", "..", "docs"
+)
+
+# The old personal repo URL that was migrated to the crewAIInc org monorepo.
+DEPRECATED_TOOLKIT_URL = "github.com/joaomdmoura/crewai-tools"
+CORRECT_TOOLKIT_URL = (
+    "github.com/crewAIInc/crewAI/tree/main/lib/crewai-tools"
+)
+
+
+def _collect_mdx_files():
+    """Collect all .mdx files under the docs directory."""
+    mdx_files = []
+    for root, _dirs, files in os.walk(DOCS_DIR):
+        for f in files:
+            if f.endswith(".mdx"):
+                mdx_files.append(os.path.join(root, f))
+    return mdx_files
+
+
+@pytest.fixture(scope="module")
+def mdx_files():
+    files = _collect_mdx_files()
+    assert files, f"No .mdx files found under {DOCS_DIR}"
+    return files
+
+
+class TestDocumentationLinks:
+    """Ensure documentation links point to the correct repositories."""
+
+    def test_no_deprecated_crewai_tools_link(self, mdx_files):
+        """Verify no docs reference the old joaomdmoura/crewai-tools repo.
+
+        The CrewAI tools have moved to the monorepo at
+        crewAIInc/crewAI/tree/main/lib/crewai-tools.
+        See: https://github.com/crewAIInc/crewAI/issues/5253
+        """
+        violations = []
+        for filepath in mdx_files:
+            with open(filepath, "r", encoding="utf-8") as fh:
+                for line_num, line in enumerate(fh, start=1):
+                    if DEPRECATED_TOOLKIT_URL in line:
+                        rel_path = os.path.relpath(filepath, DOCS_DIR)
+                        violations.append(f"  {rel_path}:{line_num}")
+
+        assert not violations, (
+            f"Found deprecated CrewAI Toolkit URL ({DEPRECATED_TOOLKIT_URL}) "
+            f"in the following doc files. "
+            f"Update to: {CORRECT_TOOLKIT_URL}\n"
+            + "\n".join(violations)
+        )
+
+    def test_crewai_toolkit_links_use_correct_url(self, mdx_files):
+        """Verify that CrewAI Toolkit markdown links point to the monorepo."""
+        pattern = re.compile(
+            r"\[.*?CrewAI.*?Toolkit.*?\]\((https?://[^)]+)\)", re.IGNORECASE
+        )
+        bad_links = []
+        for filepath in mdx_files:
+            with open(filepath, "r", encoding="utf-8") as fh:
+                for line_num, line in enumerate(fh, start=1):
+                    for match in pattern.finditer(line):
+                        url = match.group(1)
+                        if CORRECT_TOOLKIT_URL not in url:
+                            rel_path = os.path.relpath(filepath, DOCS_DIR)
+                            bad_links.append(
+                                f"  {rel_path}:{line_num} -> {url}"
+                            )
+
+        assert not bad_links, (
+            "Found CrewAI Toolkit links not pointing to the official monorepo "
+            f"({CORRECT_TOOLKIT_URL}):\n" + "\n".join(bad_links)
+        )

lib/devtools/src/crewai_devtools/__init__.py

@@ -1,3 +1,3 @@
 """CrewAI development tools."""
 
-__version__ = "1.13.0a7"
+__version__ = "1.13.0"

uv.lock

@@ -2,14 +2,22 @@ version = 1
 revision = 3
 requires-python = ">=3.10, <3.14"
 resolution-markers = [
-    "python_full_version < '3.11' and platform_python_implementation == 'PyPy'",
-    "python_full_version < '3.11' and platform_python_implementation != 'PyPy'",
-    "python_full_version == '3.11.*' and platform_python_implementation == 'PyPy'",
-    "python_full_version == '3.11.*' and platform_python_implementation != 'PyPy'",
-    "python_full_version == '3.12.*' and platform_python_implementation == 'PyPy'",
-    "python_full_version == '3.12.*' and platform_python_implementation != 'PyPy'",
-    "python_full_version >= '3.13' and platform_python_implementation == 'PyPy'",
-    "python_full_version >= '3.13' and platform_python_implementation != 'PyPy'",
+    "python_full_version < '3.11' and platform_machine != 's390x' and platform_python_implementation == 'PyPy'",
+    "python_full_version < '3.11' and platform_machine == 's390x' and platform_python_implementation == 'PyPy'",
+    "python_full_version < '3.11' and platform_machine != 's390x' and platform_python_implementation != 'PyPy'",
+    "python_full_version < '3.11' and platform_machine == 's390x' and platform_python_implementation != 'PyPy'",
+    "python_full_version == '3.11.*' and platform_machine != 's390x' and platform_python_implementation == 'PyPy'",
+    "python_full_version == '3.11.*' and platform_machine == 's390x' and platform_python_implementation == 'PyPy'",
+    "python_full_version == '3.11.*' and platform_machine != 's390x' and platform_python_implementation != 'PyPy'",
+    "python_full_version == '3.11.*' and platform_machine == 's390x' and platform_python_implementation != 'PyPy'",
+    "python_full_version == '3.12.*' and platform_machine != 's390x' and platform_python_implementation == 'PyPy'",
+    "python_full_version == '3.12.*' and platform_machine == 's390x' and platform_python_implementation == 'PyPy'",
+    "python_full_version == '3.12.*' and platform_machine != 's390x' and platform_python_implementation != 'PyPy'",
+    "python_full_version == '3.12.*' and platform_machine == 's390x' and platform_python_implementation != 'PyPy'",
+    "python_full_version >= '3.13' and platform_machine != 's390x' and platform_python_implementation == 'PyPy'",
+    "python_full_version >= '3.13' and platform_machine == 's390x' and platform_python_implementation == 'PyPy'",
+    "python_full_version >= '3.13' and platform_machine != 's390x' and platform_python_implementation != 'PyPy'",
+    "python_full_version >= '3.13' and platform_machine == 's390x' and platform_python_implementation != 'PyPy'",
 ]
 
 [manifest]
@@ -142,7 +150,7 @@ wheels = [
 
 [[package]]
 name = "aiohttp"
-version = "3.13.3"
+version = "3.13.5"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "aiohappyeyeballs" },
@@ -154,76 +162,76 @@ dependencies = [
     { name = "propcache" },
     { name = "yarl" },
 ]
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+sdist = { url = "https://files.pythonhosted.org/packages/77/9a/152096d4808df8e4268befa55fba462f440f14beab85e8ad9bf990516918/aiohttp-3.13.5.tar.gz", hash = "sha256:9d98cc980ecc96be6eb4c1994ce35d28d8b1f5e5208a23b421187d1209dbb7d1", size = 7858271, upload-time = "2026-03-31T22:01:03.343Z" }
 wheels = [
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 version = "12.9.4"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
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+    { name = "cuda-pathfinder", marker = "platform_machine != 's390x'" },
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-    "python_full_version >= '3.13' and platform_python_implementation != 'PyPy'",
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-    "python_full_version >= '3.13' and platform_python_implementation == 'PyPy'",
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