MCP Server Builder
anthropics/skills
Guides the design and implementation of Model Context Protocol servers in TypeScript or Python, from tool naming and error messages to evaluation.
Internal codebase and operations health check — the CTO scans technical health, the COO checks operational health.
$ npx skills add andrew-yangy/gru-ai --skill healthcheck -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install andrew-yangy/gru-ai healthcheck --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/andrew-yangy/gru-ai.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/healthcheck .claude/skills/healthcheck && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "healthcheck" agent skill from https://github.com/andrew-yangy/gru-ai/tree/main/.claude/skills/healthcheck into .claude/skills/healthcheck/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "healthcheck", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/andrew-yangy/gru-ai/tree/main/.claude/skills/healthcheckType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add andrew-yangy/gru-ai --skill healthcheck -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install andrew-yangy/gru-ai healthcheck --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/andrew-yangy/gru-ai.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/healthcheck .agents/skills/healthcheck && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "healthcheck" agent skill from https://github.com/andrew-yangy/gru-ai/tree/main/.claude/skills/healthcheck into .agents/skills/healthcheck/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "healthcheck", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add andrew-yangy/gru-ai --skill healthcheck -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install andrew-yangy/gru-ai healthcheck --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/andrew-yangy/gru-ai.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/healthcheck .cursor/skills/healthcheck && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "healthcheck" agent skill from https://github.com/andrew-yangy/gru-ai/tree/main/.claude/skills/healthcheck into .cursor/skills/healthcheck/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "healthcheck", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/andrew-yangy/gru-ai.git --path .claude/skills/healthcheck--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add andrew-yangy/gru-ai --skill healthcheck -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install andrew-yangy/gru-ai healthcheck --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/andrew-yangy/gru-ai.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/healthcheck .gemini/skills/healthcheck && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "healthcheck" agent skill from https://github.com/andrew-yangy/gru-ai/tree/main/.claude/skills/healthcheck into .gemini/skills/healthcheck/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "healthcheck", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install andrew-yangy/gru-ai healthcheckInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add andrew-yangy/gru-ai --skill healthcheck -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/andrew-yangy/gru-ai.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/healthcheck .github/skills/healthcheck && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "healthcheck" agent skill from https://github.com/andrew-yangy/gru-ai/tree/main/.claude/skills/healthcheck into .github/skills/healthcheck/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "healthcheck", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add andrew-yangy/gru-ai --skill healthcheck -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install andrew-yangy/gru-ai healthcheck --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/andrew-yangy/gru-ai.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/healthcheck .opencode/skills/healthcheck && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "healthcheck" agent skill from https://github.com/andrew-yangy/gru-ai/tree/main/.claude/skills/healthcheck into .opencode/skills/healthcheck/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "healthcheck", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
healthcheckInternal codebase and operations health check — the CTO scans technical health, the COO checks operational health.
Healthcheck is an agent skill from andrew-yangy/gru-ai. Internal codebase and operations health check — the CTO scans technical health, the COO checks operational health. Run bi-weekly to catch internal issues. Lightweight maintenance, not the main event.
Its SKILL.md is about 2.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Agent Workflows. The repository describes itself as: Autonomous AI agent team for one-man companies. Context engineering + harness engineering drive a pipeline that brainstorms, builds, reviews, and ships. The licence is MIT.
5 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 8fba479. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Healthcheck loads about 2.4k tokens when it runs. Until then it costs about 53 tokens; SKILL.md has 463 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from andrew-yangy/gru-ai at commit 8fba479, republished under its MIT licence (© andrew-yangy). 463 words, ~2,378 tokens.
.claude/skills/healthcheck/SKILL.md (or your agent's skills folder).Read .claude/agent-registry.json to map roles to agent names. Use each agent's id as the subagent_type when spawning. The CTO handles technical health; the COO handles operational health.
Run a healthcheck: the CTO scans codebase health, the COO checks operational health. Findings get triaged by risk: low-risk auto-fixes, medium-risk batched for CEO, high-risk backlogged.
This is maintenance, not strategy. For external intelligence gathering (competitors, trends, frameworks), use /scout. Healthcheck is the janitor, not the executive.
Read these before spawning agents:
.context/vision.md — guardrails (what NOT to break).context/preferences.md — CEO standing orders.context/directives/*/directive.json — current directives (to check for staleness).context/lessons/orchestration.md.context/backlog.json — what's already queued.context/reports/ — what was recently doneSpawn 2 agents in parallel: the CTO (technical) and the COO (operational).
Each agent receives:
.claude/agents/{name}.md.context/vision.md (guardrails are critical).context/preferences.md.context/directives/*/directive.json.context/backlog.json summaryBoth agents: subagent_type: "general-purpose", model: "opus"
You are the CTO. You are running a standing healthcheck of the codebase.
Your job: scan the codebase and infrastructure for internal issues.
CHECK THESE AREAS:
1. **Security**: Run `npm audit` in each app directory. Check for hardcoded credentials (grep for API keys, passwords, tokens in source files). Look for unauthed endpoints, injection vectors.
2. **Dependencies**: Check package.json files for outdated or deprecated packages. Look for packages with known CVEs.
3. **Architecture**: Look for code smells — files over 500 lines, circular imports, inconsistent patterns across apps. Check for dead code (unused exports, unreferenced files).
4. **Type safety**: Run `npm run type-check` and report any errors. Check for `any` type usage, missing type definitions.
5. **Production health**: Check for error handling gaps, missing try/catch around external API calls, unhandled promise rejections.
USE THESE TOOLS: Bash (npm audit, type-check), Grep (security patterns, dead code), Glob (file structure), Read (specific files)
DO NOT fix anything. Report findings only.
{JSON output instructions below}You are the COO. You are running a standing healthcheck of project operations.
Your job: audit project operations for stale goals, blocked work, and resource gaps.
CHECK THESE AREAS:
1. **Directive freshness**: Read all directives in `.context/directives/*/directive.json`. Are any stale (no progress in 2+ weeks)?
2. **Backlog health**: Read `.context/backlog.json`. Are items prioritized? Are there items marked done that should be cleaned up? Any duplicates?
3. **Active work**: Check `.context/directives/*/projects/*/project.json` for active projects. Is anything in progress but stuck? Any projects without recent file changes?
4. **Recent directives**: Read `.context/reports/`. Were there failures or follow-ups that haven't been addressed?
5. **Process gaps**: Check if lessons.md is up to date. Are there patterns emerging from recent work that should be captured?
6. **Backlog health (structured checks)**:
- Read `.context/backlog.json` — check for stale items older than 30 days.
- Count items per priority (P0/P1/P2). Flag any category with 0 prioritized items.
- Check for duplicate items (same item title appearing multiple times).
7. **Partially-done project detection**:
- Read ALL `.context/directives/*/projects/*/project.json` files (tasks are embedded)
- For each: count completed vs total tasks, compute completion percentage
- Flag if completion > 50% but the project's most recently modified file is > 14 days old
- Flag if completion is 100% but project status is still "active" (should be "completed")
8. **Index accuracy**:
- Verify that project statuses in project.json match actual task completion
- Flag any mismatches between directive status and project statuses
- Verify project.json files match filesystem structure
9. **Active/done duplicates**:
- Check for projects with contradictory status vs task completion
- Flag as: "project {name} has status {status} but tasks show {completion}% complete"
USE THESE TOOLS: Read (context files, reports), Glob (directive structure, projects), Grep (stale dates, TODO items)
DO NOT fix anything. Report findings only.
{JSON output instructions below}Append these instructions to each agent's prompt:
CRITICAL OUTPUT FORMAT: Your response must contain ONLY valid JSON. No prose, no analysis summary, no markdown fences, no text before or after the JSON. The very first character of your response must be `{` and the very last must be `}`.
Your output must follow this schema:
{
"agent": "cto-id | coo-id",
"domain": "technical | operations",
"healthcheck_date": "YYYY-MM-DD",
"findings": [
{
"id": "finding-slug",
"severity": "critical | high | medium | low | info",
"area": "Which area this falls under (e.g., security, dependencies, goal-freshness)",
"title": "Short description of the finding",
"detail": "What you found — be specific with file paths, line numbers, counts",
"evidence": "The grep output, command output, or file content that proves this",
"suggested_fix": "What should be done about this (1-2 sentences)",
"risk_level": "low | medium | high",
"already_tracked": "If this is already in a backlog or OKR, reference it here. Otherwise null."
}
],
"summary": "2-3 sentence overview of domain health"
}
SEVERITY GUIDE:
- critical: Active security vulnerability, data exposure, broken production feature
- high: Significant technical debt, degraded user experience, stale critical goals
- medium: Code quality issues, minor gaps, optimization opportunities
- low: Nice-to-have improvements, minor inconsistencies
- info: Observations, no action needed
RISK LEVEL (for triage):
- low: Safe to auto-fix (dead code deletion, unused import cleanup, minor config fixes)
- medium: Needs CEO awareness (dependency updates, backlog reorganization, goal reprioritization)
- high: Needs CEO decision (architectural changes, security patches, goal changes)Parse each agent's response as JSON. If any fails to parse, log the error and continue.
After both agents return, triage all findings by risk level:
.context/backlog.json/report# Healthcheck Report — {date}
## Summary
- **Technical (CTO)**: {summary}
- **Operational (COO)**: {summary}
## Auto-Fixed (low-risk)
{list of low-risk items that were automatically fixed, or "None"}
## Needs Your Approval ({count} medium-risk)
{list of medium-risk items with suggested fixes}
## Backlogged ({count} high-risk)
{list of high-risk items added to backlogs}
## All Clear
{any areas where no issues were found}Write each agent's raw JSON output to .context/healthchecks/latest/{agent}.json, overwriting any previous file.
If the latest/ directory already has files, move them to archive/{date}/ first.
Create directories if needed: mkdir -p .context/healthchecks/latest .context/healthchecks/archive
| Situation | Action |
|---|---|
| An agent's output doesn't parse as JSON | Log the error, continue with the other agent. |
| An agent finds no issues | Include their "all clear" summary. Good outcome. |
| npm audit fails to run | Note the error, skip security section. |
| Type-check fails to run | Note the error, skip type safety section. |
| All findings are low-risk | Auto-fix all, report clean bill of health. |
© andrew-yangy, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in .claude/skills/healthcheck of andrew-yangy/gru-ai.
Open the folder on GitHubat commit 8fba479
Healthcheck next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Healthcheck this skillandrew-yangy/gru-ai | 155 | — | ~2.4k | Automated safety check: Pass | MIT | |
| MCP Server Builderanthropics/skills | 180k | 63 repos | ~2.3k | Automated safety check: Pass | Apache-2.0 | |
| Hook Development for Claude Code Pluginsanthropics/claude-plugins-official | 38k | 10 repos | ~4.1k | Automated safety check: Notes | Apache-2.0 | |
| Using Superpowersfarm-fe/farm | 5.6k | 36 repos | ~1.4k | Automated safety check: Pass | MIT | |
| Executing Plans Inlineobra/superpowers | 297k | 2 repos | ~5.1k | Automated safety check: Pass | MIT | |
| Skill CreatorAzure/azqr | 796 | 89 repos | ~8.2k | Automated safety check: Pass | Apache-2.0 |
anthropics/skills
Guides the design and implementation of Model Context Protocol servers in TypeScript or Python, from tool naming and error messages to evaluation.
anthropics/claude-plugins-official
Explains how to write Claude Code plugin hooks, both prompt-based checks and bash commands, for events such as PreToolUse, Stop and SessionStart.
farm-fe/farm
A skill your agent uses when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions
obra/superpowers
Has the agent carry out an implementation plan itself, task by task in the current session, keeping a ledger, proving each step with a test and ending with one whole-branch review.
Azure/azqr
Create new skills, modify and improve existing skills, and measure skill performance.
anthropics/claude-plugins-official
Explains how to write agents for Claude Code plugins: the markdown file with YAML frontmatter, trigger descriptions, model and color settings, and system prompt design.
andrew-yangy/gru-ai
Provides comprehensive code review guidance for React 19, Vue 3, Rust, TypeScript, Java, Python, and C/C++.
andrew-yangy/gru-ai
Full website SEO audit with parallel subagent delegation. An agent skill from andrew-yangy/gru-ai.
andrew-yangy/gru-ai
Structured brainstorm — from quick Socratic refinement to full C-suite strategy sessions.
andrew-yangy/gru-ai
CEO dashboard with progressive disclosure — 3 tiers: headline (5 lines, default), summary (per-goal detail), deep (full weekly analysis).
andrew-yangy/gru-ai
Pipeline end-to-end smoke test -- creates a trivial directive, runs it through /directive, validates every pipeline step, and reports pass/fail with evidence.
andrew-yangy/gru-ai
Execute work through the directive pipeline — evaluate, plan, cast agents, build, review, and report.
Categories
Internal codebase and operations health check — the CTO scans technical health, the COO checks operational health. Healthcheck is an agent skill from andrew-yangy/gru-ai. Internal codebase and operations health check — the CTO scans technical health, the COO checks operational health.
Healthcheck fits situations like: agent Workflows work in your project.
Run `npx skills add andrew-yangy/gru-ai --skill healthcheck -a claude-code`. Or copy the skill folder (.claude/skills/healthcheck in andrew-yangy/gru-ai) into .claude/skills/healthcheck in your project. Claude Code loads it when a task matches its description.
Run `npx skills add andrew-yangy/gru-ai --skill healthcheck -a codex`. Or copy the skill folder (.claude/skills/healthcheck in andrew-yangy/gru-ai) into .agents/skills/healthcheck in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add andrew-yangy/gru-ai --skill healthcheck -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/healthcheck, .gemini/skills/healthcheck, .github/skills/healthcheck and .opencode/skills/healthcheck in your project.
SKILL.md names no scripts, command-line tools or credentials: Healthcheck is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Healthcheck is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.4k tokens (SKILL.md is roughly 9.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Healthcheck: MCP Server Builder (anthropics/skills, 180k stars), Hook Development for Claude Code Plugins (anthropics/claude-plugins-official, 38k stars), Using Superpowers (farm-fe/farm, 5.6k stars) and Executing Plans Inline (obra/superpowers, 297k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
andrew-yangy (a GitHub user) maintains it in andrew-yangy/gru-ai, which has 155 GitHub stars. The repository holds 9 skills in this directory. The repository was last updated on March 11, 2026.
Source: andrew-yangy/gru-ai on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.