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Ai Agent Mcp

skill-skryx-l-a-project-kit-ai-agent-mcp · by Skryx-L-A

Build/set up an AI meta-tooling project — a Claude Code skill, a subagent, an MCP server, or an agent app — from the user's grilled answers. Project-kit sub-skill loaded by new-project routing whenever someone wants to build a skill, write a subagent, stand up an MCP server, or ship an agent/LLM app. Chains skill-creator + claude-api, picks the right Claude model, and bakes in an eval plan so tri…

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Install

$ agentstack add skill-skryx-l-a-project-kit-ai-agent-mcp

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets Used
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

ai-agent-mcp — the agent/meta-tooling builder sub-skill

What this sub-skill is for

Standing up tooling that Claude (or another agent) runs: a Claude Code skill (a folder with SKILL.md), a subagent (a .md in .claude/agents/ with frontmatter + system prompt), an MCP server that exposes tools/resources, or a small agent app built on the Anthropic SDK. This is the user's home turf — he builds skills and agents heavily — so the bar is high: correct triggering, validated tools, and evals that prove it.

Mandatory grill-questions (fold into the Definition of Ready)

Lock these before any code:

  • Form factor — skill vs. subagent vs. MCP server vs. agent app? They have different shapes,

runtimes, and "done" bars. If unsure, decide from how it's invoked (Claude reads a SKILL.md → skill; Claude delegates a scoped job → subagent; a tool surface other clients call → MCP; a standalone program driving the model → agent app).

  • Trigger surface (skills/subagents) — what user phrasing or task shape must fire it, and what

must NOT? The description line is the trigger; write it to match real intent, avoid false fires.

  • Claude model — chain claude-api for current model ids: claude-opus-4-8 (most capable),

claude-sonnet-4-6, claude-haiku-4-5-20251001, claude-fable-5. Default to the newest/most capable that fits cost+latency; justify the pick.

  • Tools / permissions — exactly which tools the skill/subagent/MCP gets, and the least-privilege

set. For MCP: which tools/resources/prompts, their input schemas, and side-effect scope.

  • Eval plan — what "works" means as runnable checks (trigger-accuracy cases, golden tool calls,

refusal cases). No eval plan = not Ready.

  • Distribution — local-only, committed into a repo's .claude/, or published/installable?
  • State & secrets — does it need state, files, or API keys? Where do keys live (never committed)?

Project sub-agents to generate (into .claude/agents/)

  • skill-author (delegate-by-default) — authors/edits SKILL.md (frontmatter name+description +

body) and subagent .md files to the kit's conventions; chains the skill-creator skill.

  • eval-runner (delegate-by-default) — builds and runs the eval suite (trigger accuracy, tool-call

goldens, variance analysis), reports pass/fail honestly, blocks "done" on red.

  • mcp-tool-designer — designs MCP tool/resource schemas, names, and input validation; verifies each

tool against the SDK reference and a smoke call.

  • prompt-author — writes/tightens the system prompt and description line; reduces false triggers.

Tools / CLIs / MCP / skills needed

Check in environment-readiness; offer install, never auto-install:

  • Node 20+ (MCP TypeScript SDK: @modelcontextprotocol/sdk) and/or Python 3.11+ (mcp,

anthropic). npx @modelcontextprotocol/inspector to test an MCP server interactively.

  • Anthropic SDKnpm i @anthropic-ai/sdk or pip install anthropic; ANTHROPIC_API_KEY for

agent apps (ask the user to paste it; never invent).

  • CHAIN these GLOBAL skills automatically: skill-creator (author skills/subagents + run/measure

evals), claude-api (model ids, params, tool-use, MCP, caching — read it before touching any model id or LLM behaviour), update-config (wire skills/MCP/hooks into settings.json), code-review

  • verify before "done". Use cli-anything if the agent app needs to drive a GUI tool headlessly.
  • MCP to chain: the kit's own MCP servers as live references — e.g. n8n (get_sdk_reference),

claude-in-chrome / playwright, Supabase — to study real tool-surface design.

File / asset nudges (on top of the base set)

Beyond CLAUDE.md, PROJEKT_.md, TASKS.md, DONE.md, README, .claude/:

  • Skill: SKILL.md (frontmatter + body), optional references/, scripts/, assets/.
  • Subagent: .claude/agents/.md (frontmatter name, description, tools + system prompt).
  • MCP server: src/server.ts (or server.py), tool/resource definitions, package.json /

pyproject.toml, a mcp.json / install snippet, and .mcp.json registration example.

  • Agent app: src/agent.*, a tool registry, a run loop, .env.example (keys, never the real .env).
  • evals/ — eval cases + a runner + a results log; this is non-optional here.
  • examples/ — sample invocations / transcripts showing the intended trigger and output.

Stack defaults & done-bar

Default stack: skill/subagent = plain Markdown to kit conventions. MCP server = TypeScript on the @modelcontextprotocol/sdk (Python mcp if the surrounding code is Python). Agent app = @anthropic-ai/sdk with the newest capable model (default claude-opus-4-8, drop to claude-sonnet-4-6 for cost/latency), tool-use loop, prompt caching where it pays. Evals via skill-creator's harness.

"Finished/working" means (checkable bar):

  • Skill/subagent: triggers on the intended phrasing and stays quiet on near-misses (eval trigger-accuracy

passes); frontmatter valid; body follows kit format.

  • MCP server: starts; every tool validates against its schema and returns a correct smoke-test result in

the Inspector; resources/prompts resolve; registration snippet works in a real client.

  • Agent app: runs the loop end-to-end against the live API, calls tools correctly, handles errors/refusals.
  • Evals pass (trigger accuracy + tool-call goldens + refusal cases) and are committed.
  • code-review + verify clean; README shows install + one real example.

Guardrails

  • Evals are the gate — "it triggered once for me" is not done; prove it with the suite.
  • Least privilege — give a skill/subagent/MCP only the tools it needs; document why each is granted.
  • Never hardcode or guess model ids/pricing/params — read claude-api; default to the newest capable model.
  • Secrets never committed.env.example only; ask the user to supply real keys.
  • No emojis in any app/tool UI or output (user's standing rule) — typographic symbols only.
  • Honest descriptions — the description line must reflect what the tool actually does and fires on; no

over-broad triggers that hijack unrelated requests.

  • Commits under the user's name only (Skryx-L-A); never add Claude as co-author.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.