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ClawHub Agent Skills author: Peter Steinberger v1.0.0 2 files body ≈ 532 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

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As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches

ProcedureSlackWriting and documentsOperations and projectstype 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
C
74/100
safety, quality, tests
Safety 60%
100
Quality 40%
84
Run on models
52
No improvement model run: 61% with skill · 36% without
Process rating
C
51/100
Has gaps
Result and completion w 14
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: slack (ClawHub)

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 · 0

    ✓ No critical or high findings

    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 51/100

    • 0Result and completion. Does not say what the result is
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 7 mutating operations with no state check
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 5 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 532 tokens

    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 152: enough signal without eating the budget
    • +4Structure: 17 headings
    • +3Step-by-step instructions: 5 items
    • +4Has examples (11 code blocks)

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

    Model run · 9 Sept 2026

    With the skill
    61%
    +25 pp vs baseline
    Without the skill (baseline)
    36%
    triggers: +100% / −100%

    No improvement Pass rate 61% is below threshold 80% · 7 cases · $0.038

    External checks

    ClawHub: clean
    This Slack skill clearly documents Slack bot actions and does not show hidden code, installation behavior, persistence, or unrelated data handling.
    LLM: benign (high) · VirusTotal: benign · 10 Sept 2026