Review Clawhub Profile Proposal logo

Review Clawhub Profile Proposal

Organization
openclaw
review-clawhub-profile-proposal

Use when an OpenClaw maintainer or owner is reviewing a ClawHub malicious-skill profile proposal PR: checking `proposals/<GHSA-ID>/clawscan.yml`, reading the private vulnerability context without leaking it, running the SkillTrustBench Profile Gate or equivalent local benchmark, updating the accepted baseline, and promoting an accepted candidate into `internal/profiles/clawhub/clawscan.yml`.

Overview

Publisheropenclaw
Repositoryclawscan
Skill namereview-clawhub-profile-proposal
Stars
150
Forks
28
Bundled files
1
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.

  • 1 bundled files

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

  • Open source

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

Installation

Install the Review Clawhub Profile Proposal 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/clawscan/tree/main/skills/review-clawhub-profile-proposal
  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/clawscan.git /tmp/clawscan
mkdir -p .claude/skills
cp -r /tmp/clawscan/skills/review-clawhub-profile-proposal .claude/skills/review-clawhub-profile-proposal
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Review Clawhub Profile Proposal 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 Review Clawhub Profile Proposal 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 Review Clawhub Profile Proposal 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.

Review ClawHub Profile Proposal

Overview

Use this owner-side workflow for a public PR that proposes a candidate ClawHub profile at proposals/<GHSA-ID>/clawscan.yml after a private vulnerability report. The goal is to validate the candidate, keep sensitive details private, and, if accepted, promote the public profile behavior into the bundled internal/profiles/clawhub/clawscan.yml.

Safety Boundary

  • Treat the GitHub private vulnerability report as the source for sensitive malicious skill details.
  • Do not paste live exploit details, private report text, private artifacts, or suspicious skill payloads into public PR comments, public docs, commit messages, or committed baseline summaries.
  • The public proposal PR should start with only proposals/<GHSA-ID>/clawscan.yml. Do not trust it until reviewed.
  • Do not run the suspicious skill. ClawScan scans skill files as data; it should not execute the skill's behavior.
  • Do not promote a candidate unless the private report, proposal diff, and benchmark proof all line up.

Review Workflow

  1. Read the current repo and PR state.

    • Check git status --short --branch before editing.
    • Fetch the PR branch and inspect the changed files.
    • Confirm the public PR initially contains only proposals/<GHSA-ID>/clawscan.yml plus any baseline summary commit produced by the maintainer gate.
    • Confirm the proposal file defines a clawhub profile.
    • Confirm the proposal does not edit official bundled profile files yet: internal/profiles/clawhub/clawscan.yml, internal/profiles/clawhub/prompt.md, or internal/profiles/clawhub/output.schema.json.
  2. Read the private report privately.

    Use the private vulnerability report only to understand:

    • what malicious behavior must be caught
    • why the current built-in clawhub profile misses or under-detects it
    • what evidence should be preserved privately
    • whether any proposal text or config comments leak sensitive details

    Keep public comments high-level, such as "validated against the private report" or "needs private-case follow-up"; do not quote private details.

  3. Validate the candidate profile.

    Prefer the manual GitHub Actions workflow when available:

    text
    SkillTrustBench Profile Gate

    Dispatch it with the PR number and proposal path. It should run:

    bash
    clawscan benchmark SkillTrustBench \
      --ids https://huggingface.co/datasets/cuhk-zhuque/SkillTrustBench-results/resolve/main/data/evaluation_subset_10pct.jsonl \
      --config proposals/<GHSA-ID>/clawscan.yml \
      --profile clawhub \
      --output ./artifacts/skilltrustbench-candidate.json

    If running locally, use the same command. The --ids source is the public SkillTrustBench leaderboard subset and is mutually exclusive with --limit and --offset.

  4. Review the benchmark artifact.

    Check:

    • the artifact is full JSON and preserved as a workflow artifact or private maintainer artifact
    • benchmark.id is cuhk-zhuque/SkillTrustBench
    • benchmark.split is benchmark
    • benchmark.idsCount is 556
    • benchmark.idsSha256 matches the planned subset hash 903a036e4b7b16ee28e22d5d9db57a00b3764cfe41e43144acad67921e5196c2
    • scanner and judge statuses are acceptable
    • evaluation metrics are not an unacceptable regression
    • the candidate catches the private reported behavior when private proof is available
  5. Update the accepted baseline summary.

    Use the repo script so the compact baseline is generated from the full candidate artifact:

    bash
    go run ./scripts/update-skilltrustbench-baseline \
      --artifact ./artifacts/skilltrustbench-candidate.json \
      --output benchmarks/skilltrustbench-leaderboard-10pct/<YYYY-MM-DD>.json \
      --profile clawhub \
      --profile-source proposals/<GHSA-ID>/clawscan.yml \
      --subset-case-ids-sha256 903a036e4b7b16ee28e22d5d9db57a00b3764cfe41e43144acad67921e5196c2 \
      --workflow-url <workflow-url>

    If the PR merges, the newest dated JSON file in benchmarks/skilltrustbench-leaderboard-10pct/ is the latest accepted baseline for the bundled clawhub profile. The script fails if the candidate artifact's selected-ID hash does not match the planned subset. No post-merge rerun is required.

  6. Decide.

    If rejected:

    • leave a public PR comment with non-sensitive reasons
    • keep details that identify the malicious payload in the private report
    • do not edit official bundled profile files

    If accepted:

    • promote the accepted public clawhub profile behavior into internal/profiles/clawhub/clawscan.yml
    • add a dated baseline under benchmarks/skilltrustbench-leaderboard-10pct/ from the candidate artifact in the same PR
    • preserve or remove proposals/<GHSA-ID>/clawscan.yml according to the issue/PR instruction; default to preserving it as public proposal trail unless the maintainer explicitly chooses to remove it
    • keep prompt/schema changes maintainer-owned; edit internal/profiles/clawhub/prompt.md or internal/profiles/clawhub/output.schema.json only when that is the accepted change
  7. Verify the promoted built-in profile.

    Run at least:

    bash
    go test -count=1 ./...
    go vet ./...
    go run ./cmd/clawscan profiles -v
    go run ./cmd/clawscan --help

    For benchmark proof after promotion, run:

    bash
    clawscan benchmark SkillTrustBench \
      --ids https://huggingface.co/datasets/cuhk-zhuque/SkillTrustBench-results/resolve/main/data/evaluation_subset_10pct.jsonl \
      --profile clawhub \
      --output ./artifacts/skilltrustbench-clawhub.json

    Use a smaller proof only when explicitly accepted; the official gate uses the subset ID source above.

  8. Update the PR.

    • Push the promotion commit to the PR branch if that is the chosen review path.
    • Keep the PR body/comments free of private exploit details.
    • Add proof with commands, artifact links, and residual risk.

Promotion Patch Shape

The maintainer promotion commit usually touches:

text
internal/profiles/clawhub/clawscan.yml
benchmarks/skilltrustbench-leaderboard-10pct/<YYYY-MM-DD>.json

It may also touch:

text
internal/profiles/clawhub/prompt.md
internal/profiles/clawhub/output.schema.json
docs/
tests

Do not include private artifacts, malicious payload details, or generated dist/ output in ordinary promotion commits unless the issue explicitly asks for them.

Handoff Shape

End with:

  • verdict: accepted, rejected, or blocked
  • proposal path and PR/ref reviewed
  • private report checked, without sensitive details
  • benchmark command and artifact location
  • baseline summary update status
  • bundled profile files changed
  • exact verification commands and results
  • commit SHA or reason no commit was created
  • residual risk and next owner action

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 Review Clawhub Profile Proposal AI skill do?

Use when an OpenClaw maintainer or owner is reviewing a ClawHub malicious-skill profile proposal PR: checking `proposals/<GHSA-ID>/clawscan.yml`, reading the private vulnerability context without leaking it, running the SkillTrustBench Profile Gate or equivalent local benchmark, updating the accepted baseline, and promoting an accepted candidate into `internal/profiles/clawhub/clawscan.yml`.

Why use Review Clawhub Profile Proposal on TypingMind?

Because you install it once and use it with any model. Review Clawhub Profile Proposal 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 Review Clawhub Profile Proposal in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/openclaw/clawscan/tree/main/skills/review-clawhub-profile-proposal. 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 Review Clawhub Profile Proposal?

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 Review Clawhub Profile Proposal?

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

Is the Review Clawhub Profile Proposal AI skill free?

Yes. It is published on GitHub by openclaw 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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