agentleFS
Sign inStart free
Microsoft AzureKnown publisherAzure/agent-app-mcp/.github/skills/mcp-capability-development/SKILL.md

mcp-capability-development

Skill22 starsChanged 10 days agoMITView on GitHub

Designs and implements safe GPT-RAG MCP tools, resources, prompts, and registrations. Use whenever a runtime MCP capability or its orchestrator-facing contract changes.

1 other project uses a version of this.

Adopted by

Most recently taken up by

  • Other versions1 project uses a version of this.

    Word for word · 1

    1. Azure/gpt-rag-mcp★ 22100% same

    Edited · 0

    None found.

    Wrote their own version · 0

    None found.

    How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.

  • In this repository7 other files it gives its agents.

The file

We split this skill into the rules it gives an agent

6 rules. About 0 are common, 4 are distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈4

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Put focused logic in src/tools/, src/resources/, or src/prompts/ and keep registration in src/server.py thin.

    line 14
  2. Distinctive:

    Treat all inputs and upstream content as untrusted.

    line 16
  3. Distinctive:

    Add timeouts, output limits, least-privilege access, and actionable non-sensitive errors at external boundaries.

    line 18
  4. Distinctive:

    Add focused behavior or contract tests when feasible.

    line 22
  5. Distinctive:

    Update this repository's documentation and the GPT-RAG docs branch when users or operators observe the change.

    line 26
  6. Very specific:

    Never place this runtime capability under .github/.

    line 29

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

MCP capability development

  1. Classify the capability as a tool, resource, prompt, or transport concern and confirm Azure/gpt-rag-mcp owns it.
  2. Identify the orchestrator outcome, trust boundary, authorization model, external effects, limits, and compatibility constraints.
  3. Define a narrow typed contract: name, description, arguments, defaults, validation, result shape, error behavior, and bounds.
  4. Put focused logic in src/tools/, src/resources/, or src/prompts/ and keep registration in src/server.py thin.
  5. Treat all inputs and upstream content as untrusted. Validate schemes, hosts, identifiers, paths, sizes, and counts before effects.
  6. Add timeouts, output limits, least-privilege access, and actionable non-sensitive errors at external boundaries.
  7. Preserve compatibility or document and coordinate migration with the orchestrator and Azure/GPT-RAG.
  8. Add focused behavior or contract tests when feasible.
  9. Restore with uv sync, check import or startup behavior, exercise the capability with the MCP Inspector, and run orchestrator end to end when the integration contract changes.
  10. Update this repository's documentation and the GPT-RAG docs branch when users or operators observe the change.

Never place this runtime capability under .github/; that directory contains engineering-time Copilot assets only.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

Reviews can't be read right now.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

Check your setup, free