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AB multi-capability-bug-closure

Unified bug investigation and closure by combining source code, database, server logs, and software platform query capabilities. Use when users require evidence-based conclusions from real data rather than static code analysis only.

ClawHub Agent Skills author: hgvgfgvh v1.0.0 MIT-0 2 files body ≈ 1 190 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process B 79/100 · Nearly there — weak spots: consistency

AnalyzerSoftware developmentInfrastructuretype 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
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
87
Run on models
none yet
Process rating
B
79/100
Nearly there
Consistency w 8
40
Result and completion w 14
60
Failures and branches w 10
60
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: 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 79/100

    • 40Consistency. Frontmatter name (multi-capability-bug-closure) differs from the folder (multi-capability-bug-closure-en)
    • 60Result and completion. Output format stated, no completion criterion
    • 60Failures and branches. 2 branches
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 39 steps
    • 100Execution cost. Instruction body is 1190 tokens
    • 100Running it twice. No mutating operations
    • 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)
    • +1No license
    • +2Single-language instructions
    • +3Description length 232: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 39 items
    • +3Output format is stated explicitly
    • +4Has examples (1 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.

    External checks

    ClawHub: clean
    The skill content is coherent and purpose-aligned, with disclosed use of local development, review, Convex, GitHub, and ClawHub moderation tooling.
    LLM: benign (medium) · VirusTotal: · 29 May 2026