Agent skill

Healthcheck

by andrew-yangy in andrew-yangy/gru-ai

Internal codebase and operations health check — the CTO scans technical health, the COO checks operational health.

MITAuto-check passedAgent Workflows

Install Healthcheck

skills CLI
$ npx skills add andrew-yangy/gru-ai --skill healthcheck -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install andrew-yangy/gru-ai healthcheck --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ 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-src

Use ~/.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/

Facts

Skill name
healthcheck
GitHub stars
155
Token cost
~2.4k tokens
SKILL.md length
463 words
Files
1
Skills in repo
9
Repo updated
First seen
Licence
MIT

At a glance

Internal codebase and operations health check — the CTO scans technical health, the COO checks operational health.

  • Works in 5 steps: Read Context → Spawn Healthcheck Agents (Parallel) → Triage Findings → …
  • Agent Workflows work in your project
  • SKILL.md covers Role Resolution, Step 1: Read Context, Step 2: Spawn Healthcheck… and Step 3: Triage Findings, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

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.

When your agent uses it

  • Agent Workflows work in your project

Example prompts

  • “/healthcheck”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Read Context
  2. Spawn Healthcheck Agents (Parallel)
  3. Triage Findings
  4. Present Results
  5. Save Results

What it can do on your machine

Read from SKILL.md and the folder at commit 8fba479. It shows what the files ask for, not the result of running them.

  • Tool permissions

    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.

  • Runs code

    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.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

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.

Always · name and description, kept in context so the agent knows when to use it
~53
When it runs · the whole SKILL.md, loaded when a task matches
~2.4k

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.

Safety

Auto-check passed

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.

SKILL.md

The full file from andrew-yangy/gru-ai at commit 8fba479, republished under its MIT licence (© andrew-yangy). 463 words, ~2,378 tokens.

Download SKILL.mdSave it as .claude/skills/healthcheck/SKILL.md (or your agent's skills folder).
name
healthcheck
description
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.

Healthcheck — Internal Maintenance

Role Resolution

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.

Step 1: Read Context

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
  • Recent directive reports in .context/reports/ — what was recently done

Step 2: Spawn Healthcheck Agents (Parallel)

Spawn 2 agents in parallel: the CTO (technical) and the COO (operational).

Each agent receives:

  • Their full personality from .claude/agents/{name}.md
  • .context/vision.md (guardrails are critical)
  • .context/preferences.md
  • .context/directives/*/directive.json
  • .context/backlog.json summary
  • Recent directive report summaries (filenames + dates)

Both agents: subagent_type: "general-purpose", model: "opus"

CTO — Technical Health
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}
COO — Operational Health
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}
JSON Output Format (same for both agents)

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.

Step 3: Triage Findings

After both agents return, triage all findings by risk level:

Low-risk (auto-fixable)
  • Dead code deletion, unused imports, minor config fixes
  • Present to CEO as: "Auto-fixing {N} low-risk items: {list}"
  • Execute the fixes immediately (spawn an engineer if needed)
Medium-risk (CEO batch approval)
  • Dependency updates, backlog cleanup, stale goal flagging
  • Present as a batch: "Found {N} medium-risk items that need your approval"
  • CEO approves/rejects the batch
Show full SKILL.md (193 more words)Show less
High-risk (CEO decides)
  • Security patches, architectural changes, goal modifications
  • Add to .context/backlog.json
  • Flag for CEO attention in the next /report

Step 4: Present Results

# 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}

Step 5: Save Results

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

Failure Handling

SituationAction
An agent's output doesn't parse as JSONLog the error, continue with the other agent.
An agent finds no issuesInclude their "all clear" summary. Good outcome.
npm audit fails to runNote the error, skip security section.
Type-check fails to runNote the error, skip type safety section.
All findings are low-riskAuto-fix all, report clean bill of health.

Rules

NEVER
  • Fix high-risk issues without CEO approval
  • Skip the CTO (always run technical health)
  • Propose strategic initiatives (that's /scout's job)
  • Overwrite previous healthcheck results without archiving
ALWAYS
  • Read context files before spawning agents
  • Include personality files in agent prompts
  • Auto-fix low-risk items (that's the whole point of healthcheck being lightweight)
  • Save results to healthchecks/latest/ for /report to read
  • Keep it fast — healthcheck should complete in under 10 minutes

© 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

Files

Just SKILL.md in .claude/skills/healthcheck of andrew-yangy/gru-ai.

Open the folder on GitHubat commit 8fba479

Compare with similar skills

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.

Healthcheck compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Healthcheck this skillandrew-yangy/gru-ai155—~2.4kAutomated safety check: PassMIT
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Hook Development for Claude Code Pluginsanthropics/claude-plugins-official38k10 repos~4.1kAutomated safety check: NotesApache-2.0
Using Superpowersfarm-fe/farm5.6k36 repos~1.4kAutomated safety check: PassMIT
Executing Plans Inlineobra/superpowers297k2 repos~5.1kAutomated safety check: PassMIT
Skill CreatorAzure/azqr79689 repos~8.2kAutomated safety check: PassApache-2.0

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Categories

Questions about Healthcheck

What does Healthcheck do?

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.

When should I use Healthcheck?

Healthcheck fits situations like: agent Workflows work in your project.

How do I install Healthcheck in Claude Code?

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.

How do I install Healthcheck in Codex?

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.

Can I use Healthcheck in Cursor, Gemini CLI or GitHub Copilot?

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.

What does Healthcheck need to run?

SKILL.md names no scripts, command-line tools or credentials: Healthcheck is instructions for the agent only.

Does Healthcheck access the network?

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.

Is Healthcheck safe to install?

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.

What licence does Healthcheck use?

Healthcheck is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Healthcheck use?

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.

What are the alternatives to Healthcheck?

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.

Who maintains Healthcheck?

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.