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Discover and resolve open source GitHub issues across community repos during idle time. Finds good-first-issue/help-wanted/documentation issues, forks repos, implements fixes, and opens PRs on your behalf. Use for idle agent contribution, building GitHub profile activity, or community open source work. Usage: /oss-contributor [--repos owner/repo,...] [--labels bug,docs] [--limit 5] [--dry-run] [--auto] [--model sonnet] [--notify-channel -1002381931352]

ClawHub Agent Skills author: Kevin Bolander v1.0.0 2 files body ≈ 3 344 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 60/100 · Has gaps — weak spots: result and completion, inputs and preconditions

GeneratorGitHubInfrastructureAI and agentsWriting and documentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
81/100
safety, quality, tests
Safety 60%
79
Quality 40%
84
Run on models
none yet
Process rating
C
60/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
When it triggers w 12
50
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Exfiltration medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 5

    ✓ No critical or high findings

    Medium and low: 5
    • medium Exfiltration net-credential-use SKILL.md:16
      Credential used in a network call (verify the destination is the intended service)
      curl -s -H "Authorization: Bearer $GH_TOKEN" -H "Accept: application/vnd.github+json" ...
    • medium Exfiltration net-credential-use SKILL.md:89
      Credential used in a network call (verify the destination is the intended service)
      curl -s -H "Authorization: Bearer $GH_TOKEN" -H "Accept: application/vnd.github+json" \
    • medium Exfiltration net-credential-use SKILL.md:102
      Credential used in a network call (verify the destination is the intended service)
      curl -s -H "Authorization: Bearer $GH_TOKEN" \
    • medium Exfiltration net-credential-use SKILL.md:198
      Credential used in a network call (verify the destination is the intended service)
      curl -s -o /dev/null -w "%{http_code}" -H "Authorization: Bearer $GH_TOKEN" \
    • low Exfiltration net-credential-use SKILL.md:72
      Credential used in a network call (verify the destination is the intended service) (destination is a well-known publishing service)
      curl -s -H "Authorization: Bearer $GH_TOKEN" https://api.github.com/user | jq -r '.login'
      known service

    Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 60/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 85Steps. 38 steps, 1 vague phrases
    • 100Failures and branches. 3 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3344 tokens
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 456: enough signal without eating the budget
    • +4Structure: 21 headings
    • +3Step-by-step instructions: 38 items
    • +4Has examples (18 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

    External checks

    ClawHub: suspicious
    The skill mostly matches its open-source contribution purpose, but it needs Review because it can make public GitHub changes, run third-party repo tests, and unnecessarily reads and prints part of a local token.
    LLM: suspicious (high) · VirusTotal: suspicious · 28 May 2026