Marketplace Health Check logo

Marketplace Health Check

CommunityPopular
daymade
marketplace-health-check

Runs a 6-dimension evidence-based health audit of this skills marketplace repo — code safety, docs/SSOT, security/PII, PR/issue triage, manifest integrity — via a parallel workflow, then verifies findings by priority. Use for 全面体检 / 检查仓库状态 / 审计一下仓库, a pre-release sweep, or "is this repo OK" even without saying "workflow". Not for building marketplace.json (use marketplace-dev) or cache drift (use skill-governance).

Overview

Publisherdaymade
Repositoryclaude-code-skills
Skill namemarketplace-health-check
Stars
1.4K
Forks
222
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by daymade on GitHub. Read the source before you install it.

Installation

Install the Marketplace Health Check AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/daymade/claude-code-skills/tree/main/marketplace-health-check
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/daymade/claude-code-skills.git /tmp/claude-code-skills
mkdir -p .claude/skills
cp -r /tmp/claude-code-skills/marketplace-health-check .claude/skills/marketplace-health-check
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Marketplace Health Check in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Marketplace Health Check on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Marketplace Health Check is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Marketplace Health Check

Run a comprehensive, evidence-based health check of this Claude Code skills marketplace repo using a parallel fan-out Dynamic Workflow. Six independent inspectors cover, in parallel:

  1. Code & script safety — dangerous deletes, NO-FALLBACK secret leaks, hardcoded real paths, bare except, injection, missing shebangs
  2. Documentation / SSOT consistency — version coherence across marketplace.json / README×2 / CHANGELOG / git release, skill & plugin counts, broken references, derived-value drift
  3. Security / PII — keyword-free leaks gitleaks can't catch (real names, private domains), the .security-scan-passed marker gap, case-file audits
  4. Open-PR triage — classify every PR (worth-merging / needs-changes / decline-as-promotion)
  5. Open-issue triage — real bugs vs skill-requests vs promotion, plus the broken-install-command bug class
  6. Marketplace-manifest integrity — check_marketplace.sh + check_doc_skill_lists.py, orphans, suite registration

Then YOU verify the serious findings and report by priority. The bundled script (scripts/repo-health-check.workflow.js) is the proven, ready-to-run workflow; this file is how to run and interpret it.

Why a workflow — and why it MUST run inline

The six dimensions are independent, so fanning them out across six parallel agents is far faster than one agent sweeping serially, and each inspector stays focused on one concern with its own structured output.

This skill must run inline (no context: fork). It orchestrates parallel agents through the Workflow tool, and a forked subagent cannot spawn subagents or launch a workflow — running it forked would silently break the fan-out. The Workflow tool also requires explicit user opt-in; a user asking to "run the health check" IS that opt-in, so proceed.

How to run

Step 1 — Scout the current scale (one quick pass, shared by all six agents)

The workflow script takes an args object so all agents share one accurate snapshot instead of each re-discovering it. Gather:

bash
gh repo view --json nameWithOwner,stargazerCount,isPrivate | jq -c .
echo "skills: $(find . -name SKILL.md -not -path '*-workspace/*' | wc -l | tr -d ' ')"
echo "open PRs: $(gh pr list --state open --json number | jq length)"
echo "open issues: $(gh issue list --state open --json number | jq length)"
grep -A1 '"metadata"' .claude-plugin/marketplace.json | grep -oE '"version": "[^"]*"' | head -1
git rev-parse --short HEAD; gh release view --json tagName -q .tagName 2>/dev/null

Confirm isPrivate: false before treating PII as a publishing risk — the whole point is that this is a PUBLIC repo.

Step 2 — Launch the workflow

Read the bundled script and launch it inline via the script parameter (pass its contents, so there's no dependency on where the skill is installed):

Workflow({
  script: <full contents of scripts/repo-health-check.workflow.js>,
  args: { repo: "<owner/name>", scale: "<one-line summary from Step 1>" }
})

It runs the six inspectors in parallel (~15-20 min, ~400-500k output tokens — tell the user the cost up front) and returns { checks: [...] }, one structured result per dimension: health + summary + findings[] (each with severity / title / detail / location / recommendation) + stats.

While it runs you can do other useful prep, but don't start editing files the inspectors are reading.

Step 3 — Counter-Review the serious findings BEFORE reporting

Agent findings are HYPOTHESES, not conclusions. Never relay them verbatim. For every high/critical finding, verify it yourself with a quick command — grep the leaked value, sed -n the broken line, gh repo view the claimed state — confirming it's (a) real, (b) located where the agent says, and (c) not over-reach. This catches false alarms AND, just as important, agent recommendations that are actively wrong. (In the session this skill was distilled from, a security inspector recommended adding the real private domains into the public .gitleaks.toml — an anti-target move that had to be rejected; see the methodology reference.)

Filter every finding through four questions: probability (does it really happen?), cost (fix vs ignore), real scenario (does it bite in practice?), verifiable (can a 1-line command confirm or refute it?).

Report format

Lead with the table, then layer by priority. Classify — don't dump:

  • One-line verdict + a 6-dimension health table (good / minor-issues / needs-attention / critical per dimension)
  • 🔴 Must-fix — each VERIFIED high/critical, with exact location + a concrete fix
  • 🟠 Backlog — PR/issue triage outcomes, scan-marker gaps (decisions, often outward-facing — flag that they affect external contributors)
  • 🟢 Optional — low/info nits, one line each
  • 💡 Key insights — the meta-findings worth surfacing (a structural blind spot in tooling, a recurring bug class)

Tag each surfaced item ✅ real / ⚠️ partly / ❌ false-alarm. Most raw agent output is noise; your job is to surface the real risks the owner didn't already know, not to forward 25 findings for them to sift.

Judgment principles

Apply these when interpreting findings and proposing fixes. Full reasoning + the real failure cases behind each are in references/health-check-methodology.md — read it before acting on PII or PR/issue findings.

  • Anti-target: never "fix" a PII leak by listing the real value in a public allowlist (e.g. the repo's own .gitleaks.toml) — a public list enumerating real assets is itself a leak. Sanitize the value in place; detection rules for real private values belong in the owner's private global guard, not in this public repo.
  • History note: sanitizing the working copy cleans the current version, but a pre-existing leak still sits in git history. Flag the history exposure honestly; a history rewrite (force-push) is a separate high-risk decision that affects every fork — never do it unprompted.
  • Scan marker = necessary-not-sufficient: a .security-scan-passed marker means "no known-format secret was found", NOT "sanitized". It is blind to keyword-free leaks, so pair it with a human/semantic read of any skill shipping real-data examples.
  • Mandatory version bump: any change to a skill's files requires bumping that skill's version in marketplace.json (and a CHANGELOG entry). External-contributor PRs almost always miss this — flag it, don't merge without it.
  • Promotion is declined by default: third-party directory / tool / marketplace promotion PRs and issues are declined — the repo is a personal curated marketplace, not an ecosystem directory. The decline-policy template is a reference doc at the repo root (outside this skill's bundle).

Bundled resources

  • scripts/repo-health-check.workflow.js — the six-inspector Dynamic Workflow. Run it via the Workflow tool's script param (Step 2). Edit it when you add/retire an inspector dimension.
  • references/health-check-methodology.md — the Counter-Review filter, reporting discipline, and the anti-target / history / scan-marker / decline rules, each with the real failure case that motivated it.

Next step

After delivering the report, the typical follow-ups are owner decisions, not automated actions — fixing the verified HIGHs (sanitize PII, correct broken commands), or triaging the PR/issue backlog. Surface them as options; don't auto-fix or auto-comment on PRs/issues without the user's go-ahead, since those are outward-facing and affect external contributors.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Marketplace Health Check AI skill do?

Runs a 6-dimension evidence-based health audit of this skills marketplace repo — code safety, docs/SSOT, security/PII, PR/issue triage, manifest integrity — via a parallel workflow, then verifies findings by priority. Use for 全面体检 / 检查仓库状态 / 审计一下仓库, a pre-release sweep, or "is this repo OK" even without saying "workflow". Not for building marketplace.json (use marketplace-dev) or cache drift (use skill-governance).

Why use Marketplace Health Check on TypingMind?

Because you install it once and use it with any model. Marketplace Health Check is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Marketplace Health Check in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/daymade/claude-code-skills/tree/main/marketplace-health-check. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Marketplace Health Check?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Marketplace Health Check?

As many as you like. As long as a model supports skills, you can use Marketplace Health Check with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Marketplace Health Check AI skill free?

Yes. It is published on GitHub by daymade under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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