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After a traced run, crewAI printed a panel with the execution id and a viewer link. The id is internal, and the panel exposed it for no purpose a user has. Nothing is printed now. Instead, once the run's spans have reached Wharf, crewAI writes `.crewai/last_run.json` in the project: the execution id, when the run started and ended, whether it was traced anonymously or under an account, and the AMP base url. `crewai eval` reads it back, so the user evaluates their last run without pasting anything. GrantSpanExporter.record_export replaces show_trace_summary at the two finish points (an authenticated run's shutdown, an anonymous run's share). Only a run whose every export succeeded is recorded — a partial export would name a run the grader could not read whole. Recording is silent in the TUI and under message suppression too, off under the test suite, and inert inside a deployment, where the platform binds the execution before crewAI's own tracing starts. The record is written atomically and a write failure never fails the run. The crew, flow and json_crew scaffolds now ignore `.crewai/` like the declarative flow scaffold already did. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
crewai-cli
CLI for CrewAI — scaffold, run, deploy and manage AI agent crews without installing the full framework.
Installation
pip install crewai-cli
This pulls in crewai-core (shared utilities) but not the crewai framework
itself, so commands that don't need a crew loaded — crewai version,
crewai login, crewai org list, crewai config *, crewai traces *,
crewai create, crewai template * — work standalone.
Commands that load a user's crew or flow (crewai run, crewai train,
crewai test, crewai chat, crewai replay, crewai reset-memories,
crewai deploy push, crewai tool publish) require crewai to be installed
in the project's environment. They print a clear error if it is missing.
To install both at once:
pip install crewai[cli]