Openclaw Ghsa Maintainer logo

Openclaw Ghsa Maintainer

OrganizationPopular
openclaw
openclaw-ghsa-maintainer

Inspect, patch, validate, publish, or confirm OpenClaw GHSA security advisories and private-fork state.

Overview

Publisheropenclaw
Repositoryopenclaw
Skill nameopenclaw-ghsa-maintainer
Stars
391K
Forks
82.2K
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Openclaw Ghsa Maintainer 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/openclaw/openclaw/tree/main/.agents/skills/openclaw-ghsa-maintainer
  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/openclaw/openclaw.git /tmp/openclaw
mkdir -p .claude/skills
cp -r /tmp/openclaw/.agents/skills/openclaw-ghsa-maintainer .claude/skills/openclaw-ghsa-maintainer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Openclaw Ghsa Maintainer 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 Openclaw Ghsa Maintainer 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 Openclaw Ghsa Maintainer 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.

OpenClaw GHSA Maintainer

Use this skill for repo security advisory workflow only. Keep general release work in release-openclaw-maintainer.

Respect advisory guardrails

  • Before reviewing or publishing a repo advisory, read SECURITY.md.
  • Ask permission before any publish action.
  • Treat this skill as GHSA-only. Do not use it for stable or beta release work.

Fetch and inspect advisory state

Fetch the current advisory and the latest published npm version:

bash
gh api /repos/openclaw/openclaw/security-advisories/<GHSA>
npm view openclaw version --userconfig "$(mktemp)"

Use the fetch output to confirm the advisory state, linked private fork, and vulnerability payload shape before patching.

Verify private fork PRs are closed

Before publishing, verify that the advisory's private fork has no open PRs:

bash
fork=$(gh api /repos/openclaw/openclaw/security-advisories/<GHSA> | jq -r .private_fork.full_name)
gh pr list -R "$fork" --state open

The PR list must be empty before publish.

Prepare advisory Markdown and JSON safely

  • Write advisory Markdown via heredoc to a temp file. Do not use escaped \n strings.
  • Build PATCH payload JSON with jq, not hand-escaped shell JSON.

Example pattern:

bash
cat > /tmp/ghsa.desc.md <<'EOF'
<markdown description>
EOF

jq -n --rawfile desc /tmp/ghsa.desc.md \
  '{summary,severity,description:$desc,vulnerabilities:[...]}' \
  > /tmp/ghsa.patch.json

Apply PATCH calls in the correct sequence

  • Do not set severity and cvss_vector_string in the same PATCH call.
  • Use separate calls when the advisory requires both fields.
  • Publish by PATCHing the advisory and setting "state":"published". There is no separate /publish endpoint.

Example shape:

bash
gh api -X PATCH /repos/openclaw/openclaw/security-advisories/<GHSA> \
  --input /tmp/ghsa.patch.json

Publish and verify success

After publish, re-fetch the advisory and confirm:

  • state=published
  • published_at is set
  • the description does not contain literal escaped \\n

Verification pattern:

bash
gh api /repos/openclaw/openclaw/security-advisories/<GHSA>
jq -r .description < /tmp/ghsa.refetch.json | rg '\\\\n'

Common GHSA footguns

  • Publishing fails with HTTP 422 if required fields are missing or the private fork still has open PRs.
  • A payload that looks correct in shell can still be wrong if Markdown was assembled with escaped newline strings.
  • Advisory PATCH sequencing matters; separate field updates when GHSA API constraints require it.
  • Public hardening/no-publish comments and draft text should avoid raw commit hashes, PR titles/numbers, and fix-mechanism summaries. Prefer patched-version fields or release-only wording; keep SHAs, PRs, and implementation notes in internal evidence.

Frequently asked questions

What does the Openclaw Ghsa Maintainer AI skill do?

Inspect, patch, validate, publish, or confirm OpenClaw GHSA security advisories and private-fork state.

Why use Openclaw Ghsa Maintainer on TypingMind?

Because you install it once and use it with any model. Openclaw Ghsa Maintainer 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 Openclaw Ghsa Maintainer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/openclaw/openclaw/tree/main/.agents/skills/openclaw-ghsa-maintainer. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Openclaw Ghsa Maintainer?

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 Openclaw Ghsa Maintainer?

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

Is the Openclaw Ghsa Maintainer AI skill free?

It is published on GitHub by openclaw. Check the repository for licensing terms. 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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