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AB claude-review

Self-review quality gate using Claude CLI. When the user says 'review your work', 'use review-work', or 'check your output', run review-work with the task summary, --context pointing to your output file/folder, and --skill pointing to the skill used (if any). You determine all arguments yourself — the user does NOT need to specify them. Requires `claude` CLI installed.

ClawHub Agent Skills author: PaperBoardOfficial v1.0.1 MIT-0 3 files · 1 script body ≈ 1 022 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process B 69/100 · Nearly there — weak spots: result and completion, running it twice, progress reporting

AnalyzerAI and agentstype 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
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
85
Run on models
none yet
Process rating
B
69/100
Nearly there
Progress reporting w 2
0
Running it twice w 4
30
Result and completion w 14
40
the three weakest of ten parameters · all ten

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: 3. 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 69/100

    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 4 mutating operations with no state check
    • 40Result and completion. Does not say what the result is
    • 60Tools and files. Uses tools (node) that frontmatter does not declare
    • 65Failures and branches. 3 branches
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 25 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1022 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
    • +2Single-language instructions
    • +3Description length 371: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 25 items
    • +4Has examples (5 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.

    External checks

    ClawHub: suspicious
    This is a real Claude-based review tool, but it can send selected work files to Claude and persist failure notes locally without per-run confirmation.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026