Install
$ agentstack add skill-skryx-l-a-project-kit-ai-agent-mcp ✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.
Security review
✓ PassedNo 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.
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-apifor 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 SDK —
npm i @anthropic-ai/sdkorpip install anthropic;ANTHROPIC_API_KEYfor
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
verifybefore "done". Usecli-anythingif 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), optionalreferences/,scripts/,assets/. - Subagent:
.claude/agents/.md(frontmattername,description,tools+ system prompt). - MCP server:
src/server.ts(orserver.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+verifyclean; 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.exampleonly; 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.
- Author: Skryx-L-A
- Source: Skryx-L-A/project-kit
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.