Add support for skills

docs/en/concepts/knowledge.mdx

@@ -25,6 +25,35 @@ For file-based Knowledge Sources, make sure to place your files in a `knowledge`
 Also, use relative paths from the `knowledge` directory when creating the source.
 </Tip>
 
+### Skills.md for Crews (CrewBase)
+
+When using the `@CrewBase` decorator and project layout (e.g. from `crewai create crew`), you can add **Skills.md** files as crew-level knowledge sources. Place one markdown file per skill under:
+
+```
+src/<project>/.agents/<skill_name>/Skills.md
+```
+
+Each `Skills.md` is loaded as a knowledge source so the crew can query it via RAG at runtime. Use `get_skills_knowledge_sources()` when building your crew:
+
+```python
+from crewai.project import CrewBase, agent, crew, task
+
+@CrewBase
+class MyCrew():
+    # ...
+
+    @crew
+    def crew(self) -> Crew:
+        return Crew(
+            agents=self.agents,
+            tasks=self.tasks,
+            process=Process.sequential,
+            knowledge_sources=self.get_skills_knowledge_sources(),
+        )
+```
+
+You can combine skills with other knowledge sources: `knowledge_sources=[*self.get_skills_knowledge_sources(), other_source]`. If the `.agents` directory is missing or has no `Skills.md` files, `get_skills_knowledge_sources()` returns an empty list. To use a different directory than `.agents`, set the class attribute `skills_directory = "my_skills"`. Skills.md support requires the `docling` package (`uv add docling`).
+
 ### Vector store (RAG) client configuration
 
 CrewAI exposes a provider-neutral RAG client abstraction for vector stores. The default provider is ChromaDB, and Qdrant is supported as well. You can switch providers using configuration utilities.

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

@@ -110,6 +110,9 @@ def create_folder_structure(name, parent_folder=None):
         (folder_path / "src" / folder_name).mkdir(parents=True)
         (folder_path / "src" / folder_name / "tools").mkdir(parents=True)
         (folder_path / "src" / folder_name / "config").mkdir(parents=True)
+        (folder_path / "src" / folder_name / ".agents" / "research").mkdir(
+            parents=True
+        )
 
     return folder_path, folder_name, class_name
 
@@ -154,6 +157,13 @@ def copy_template_files(folder_path, name, class_name, parent_folder):
             dst_file = src_folder / file_name
             copy_template(src_file, dst_file, name, class_name, folder_path.name)
 
+        # Copy Skills.md from .agents/research template
+        skills_src = templates_dir / ".agents" / "research" / "Skills.md"
+        skills_dst = src_folder / ".agents" / "research" / "Skills.md"
+        if skills_src.exists():
+            skills_dst.parent.mkdir(parents=True, exist_ok=True)
+            copy_template(skills_src, skills_dst, name, class_name, folder_path.name)
+
 
 def create_crew(name, provider=None, skip_provider=False, parent_folder=None):
     folder_path, folder_name, class_name = create_folder_structure(name, parent_folder)

lib/crewai/src/crewai/cli/templates/crew/crew.py

@@ -54,11 +54,18 @@ class {{crew_name}}():
         """Creates the {{crew_name}} crew"""
         # To learn how to add knowledge sources to your crew, check out the documentation:
         # https://docs.crewai.com/concepts/knowledge#what-is-knowledge
+        # Skills.md files under .agents/<skill_name>/ are loaded via get_skills_knowledge_sources()
 
+        skills_sources = (
+            self.get_skills_knowledge_sources()
+            if hasattr(self, "get_skills_knowledge_sources")
+            else []
+        )
         return Crew(
             agents=self.agents, # Automatically created by the @agent decorator
             tasks=self.tasks, # Automatically created by the @task decorator
             process=Process.sequential,
             verbose=True,
+            knowledge_sources=skills_sources,
             # process=Process.hierarchical, # In case you wanna use that instead https://docs.crewai.com/how-to/Hierarchical/
         )

lib/crewai/src/crewai/project/crew_base.py

@@ -178,6 +178,57 @@ def _set_mcp_params(cls: type[CrewClass]) -> None:
     cls.mcp_connect_timeout = getattr(cls, "mcp_connect_timeout", 30)
 
 
+def _set_skills_params(cls: type[CrewClass]) -> None:
+    """Set the skills directory path for the crew class.
+
+    Args:
+        cls: Crew class to configure.
+    """
+    cls.skills_directory = getattr(cls, "skills_directory", ".agents")
+
+
+def get_skills_knowledge_sources(self: CrewInstance) -> list[Any]:
+    """Discover Skills.md files under .agents/<skill_name>/ and return them as knowledge sources.
+
+    Looks for src/<project>/.agents/<skill_name>/Skills.md (relative to the crew class
+    base_directory). Each found file is wrapped in a CrewDoclingSource so the crew can
+    query it via RAG. Requires the docling package; if not installed, returns an empty list.
+
+    Returns:
+        List of knowledge sources (CrewDoclingSource instances), or empty list if
+        .agents is missing, has no Skills.md files, or docling is not installed.
+    """
+    skills_dir_name = getattr(self, "skills_directory", ".agents")
+    skills_dir = self.base_directory / skills_dir_name
+    if not skills_dir.exists() or not skills_dir.is_dir():
+        return []
+
+    try:
+        from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource
+        from crewai.knowledge.source.crew_docling_source import CrewDoclingSource
+    except ImportError:
+        logging.warning(
+            "Skills.md support requires the docling package. "
+            "Install it with: uv add docling"
+        )
+        return []
+
+    sources: list[Any] = []
+    for subdir in sorted(skills_dir.iterdir()):
+        if not subdir.is_dir():
+            continue
+        skills_md = subdir / "Skills.md"
+        if skills_md.exists():
+            try:
+                source = CrewDoclingSource(file_paths=[skills_md])
+                sources.append(source)
+            except Exception as e:
+                logging.warning(
+                    f"Could not create knowledge source for {skills_md}: {e}"
+                )
+    return sources
+
+
 def _is_string_list(value: list[str] | list[BaseTool]) -> TypeGuard[list[str]]:
     """Type guard to check if list contains strings rather than BaseTool instances.
 
@@ -731,6 +782,7 @@ _CLASS_SETUP_FUNCTIONS: tuple[Callable[[type[CrewClass]], None], ...] = (
     _set_base_directory,
     _set_config_paths,
     _set_mcp_params,
+    _set_skills_params,
 )
 
 _METHODS_TO_INJECT = (
@@ -739,6 +791,7 @@ _METHODS_TO_INJECT = (
     _load_config,
     load_configurations,
     staticmethod(load_yaml),
+    get_skills_knowledge_sources,
     map_all_agent_variables,
     _map_agent_variables,
     map_all_task_variables,

lib/crewai/src/crewai/project/wrappers.py

@@ -81,8 +81,10 @@ class CrewInstance(Protocol):
     tasks_config: dict[str, Any]
     mcp_server_params: Any
     mcp_connect_timeout: int
+    skills_directory: str
 
     def load_configurations(self) -> None: ...
+    def get_skills_knowledge_sources(self) -> list[Any]: ...
     def map_all_agent_variables(self) -> None: ...
     def map_all_task_variables(self) -> None: ...
     def close_mcp_server(self, instance: Self, outputs: CrewOutput) -> CrewOutput: ...
@@ -122,8 +124,10 @@ class CrewClass(Protocol):
     original_tasks_config_path: str
     mcp_server_params: Any
     mcp_connect_timeout: int
+    skills_directory: str
     close_mcp_server: Callable[..., Any]
     get_mcp_tools: Callable[..., list[BaseTool]]
+    get_skills_knowledge_sources: Callable[..., list[Any]]
     _load_config: Callable[..., dict[str, Any]]
     load_configurations: Callable[..., None]
     load_yaml: Callable[..., dict[str, Any]]

lib/crewai/src/crewai/utilities/llm_utils.py

@@ -148,7 +148,10 @@ def _llm_via_environment_or_fallback() -> LLM | None:
         "AWS_SECRET_ACCESS_KEY",
         "AWS_REGION_NAME",
     ]
-    set_provider = model_name.partition("/")[0] if "/" in model_name else "openai"
+    if "/" in model_name:
+        set_provider = model_name.partition("/")[0]
+    else:
+        set_provider = LLM._infer_provider_from_model(model_name)
 
     if set_provider in ENV_VARS:
         env_vars_for_provider = ENV_VARS[set_provider]

lib/crewai/tests/test_project.py

@@ -1,3 +1,5 @@
+import tempfile
+from pathlib import Path
 from typing import Any, ClassVar
 from unittest.mock import Mock, patch
 
@@ -382,3 +384,93 @@ def test_internal_crew_with_mcp():
     adapter_mock.assert_called_once_with(
         {"host": "localhost", "port": 8000}, connect_timeout=120
     )
+
+
+def test_get_skills_knowledge_sources_discovery():
+    """get_skills_knowledge_sources discovers .agents/<skill_name>/Skills.md and returns sources."""
+
+    @CrewBase
+    class SkillsCrew:
+        agents_config = "nonexistent/agents.yaml"
+        tasks_config = "nonexistent/tasks.yaml"
+        agents: list[BaseAgent]
+        tasks: list[Task]
+
+        @agent
+        def researcher(self):
+            return Agent(
+                role="Researcher",
+                goal="Research",
+                backstory="Expert researcher",
+            )
+
+        @task
+        def research_task(self):
+            return Task(
+                description="Research", expected_output="Report", agent=self.researcher()
+            )
+
+        @crew
+        def crew(self):
+            return Crew(agents=self.agents, tasks=self.tasks, verbose=True)
+
+    with tempfile.TemporaryDirectory() as tmp:
+        base = Path(tmp)
+        (base / ".agents" / "skill_a").mkdir(parents=True)
+        (base / ".agents" / "skill_b").mkdir(parents=True)
+        (base / ".agents" / "skill_a" / "Skills.md").write_text("# Skill A")
+        (base / ".agents" / "skill_b" / "Skills.md").write_text("# Skill B")
+
+        crew_instance = SkillsCrew()
+        crew_instance.base_directory = base
+        sources = crew_instance.get_skills_knowledge_sources()
+
+    # With docling installed we get 2 sources; without it we get []
+    if len(sources) == 2:
+        paths = []
+        for s in sources:
+            paths.extend(getattr(s, "file_paths", []) or getattr(s, "safe_file_paths", []))
+        path_strs = {str(Path(p).resolve()) for p in paths}
+        expected_a = str((base / ".agents" / "skill_a" / "Skills.md").resolve())
+        expected_b = str((base / ".agents" / "skill_b" / "Skills.md").resolve())
+        assert expected_a in path_strs
+        assert expected_b in path_strs
+    else:
+        assert len(sources) == 0
+
+
+def test_get_skills_knowledge_sources_missing_dir_returns_empty():
+    """get_skills_knowledge_sources returns [] when .agents does not exist."""
+
+    @CrewBase
+    class NoSkillsCrew:
+        agents_config = "nonexistent/agents.yaml"
+        tasks_config = "nonexistent/tasks.yaml"
+        agents: list[BaseAgent]
+        tasks: list[Task]
+
+        @agent
+        def researcher(self):
+            return Agent(
+                role="Researcher",
+                goal="Research",
+                backstory="Expert researcher",
+            )
+
+        @task
+        def research_task(self):
+            return Task(
+                description="Research", expected_output="Report", agent=self.researcher()
+            )
+
+        @crew
+        def crew(self):
+            return Crew(agents=self.agents, tasks=self.tasks, verbose=True)
+
+    with tempfile.TemporaryDirectory() as tmp:
+        base = Path(tmp)
+        crew_instance = NoSkillsCrew()
+        crew_instance.base_directory = base
+        sources = crew_instance.get_skills_knowledge_sources()
+
+    assert sources == []

pyproject.toml

@@ -149,6 +149,7 @@ members = [
     "lib/crewai-tools",
     "lib/devtools",
     "lib/crewai-files",
+    "testing_agents",
 ]