Ask CrewAI Docs

Answer CrewAI questions by looking up the official documentation at docs.crewai.com.

When to Use This Skill

Use this skill when:

The user asks about a CrewAI feature, parameter, or behavior not covered in detail by the other skills
You need to verify current API syntax, method signatures, or configuration options
The user hits an error and needs troubleshooting guidance from official docs
The question is about a newer or less common CrewAI feature (e.g., telemetry, testing, CLI commands, deployment, enterprise features)
You're unsure whether your knowledge is current — the docs reflect the latest published state

Do NOT use this skill when the question is clearly answered by one of the other skills (getting-started, design-agent, design-task). Those skills contain curated, opinionated guidance. This skill is for filling gaps and verifying details.

How to Query the Docs

Step 1: Fetch the docs index

The CrewAI docs site publishes an llms.txt file — a structured index of every documentation page with descriptions. Fetch it first to find the right page:

WebFetch: https://docs.crewai.com/llms.txt

This returns a categorized list of all doc pages in the format:

- [Page Title](https://docs.crewai.com/path/to/page): "Description of what the page covers"

Categories include:

API Reference — REST endpoints (kickoff, status, resume, inputs)
Concepts — agents, crews, tasks, tools, flows, memory, knowledge, LLMs, processes, training, testing
Enterprise — RBAC, SSO, automations, traces, deployment, triggers, integrations
Tools Library — 40+ tools organized by category (AI/ML, automation, cloud, database, files, search, web scraping)
MCP Integration — MCP server setup, transports, DSL, security
Examples & Cookbooks — practical implementations
Learning Paths — tutorials and advanced topics
Observability — monitoring integrations

Step 2: Fetch the relevant page

Once you identify the right page from the index, fetch its content:

WebFetch: https://docs.crewai.com/<path-from-index>

Step 3: Synthesize and cite

Combine what you find from the docs with context from the other skills to give a clear, actionable response. Always include the docs URL so the user can read further.

Workflow Summary

Understand the user's question — what specific CrewAI concept, API, or behavior are they asking about?
Fetch llms.txt — scan the index to find the most relevant page(s)
Fetch the page(s) — retrieve the actual documentation content
Synthesize the answer — combine docs content with context from other skills
Cite the source — include the docs URL in your response

For an Even Better Experience

Users who frequently query CrewAI docs can configure the CrewAI docs MCP server in their coding agent for richer, structured search:

https://docs.crewai.com/mcp

This is optional — the llms.txt workflow above works without any setup.

Examples of Good Use Cases

User Question	Why This Skill
"What parameters does `Crew()` accept?"	Specific API reference — docs are authoritative
"How do I set up telemetry in CrewAI?"	Niche feature not covered in other skills
"What's the difference between `Process.sequential` and `Process.hierarchical`?"	Detailed comparison best sourced from docs
"I'm getting `ValidationError` when using `output_pydantic`"	Troubleshooting — docs may have known issues or caveats
"How do I deploy a CrewAI flow to production?"	Deployment guidance lives in docs, not in design skills
"What CLI commands does `crewai` support?"	CLI reference is a docs concern
"How do I configure memory for a crew?"	Detailed config options beyond what design-agent covers
"What tools are available for web scraping?"	Tools library reference
"How do I set up SSO for CrewAI enterprise?"	Enterprise features live in docs

Related Skills

getting-started — project scaffolding, choosing abstractions, Flow architecture
design-agent — agent Role-Goal-Backstory, parameter tuning, tools, memory & knowledge
design-task — task descriptions, expected_output, guardrails, structured output, dependencies

ask-docs