SKILLEMALL.ai

AC code-analysis

This skill should be used when the user needs to analyze Git repositories, compare developer commit patterns, work habits, development efficiency, code style, code quality, and slacking behaviors. It generates honest, direct developer evaluations with scores, grades, strengths, weaknesses, and actionable suggestions. Trigger phrases include "analyze code", "analyze repository", "compare developers", "code quality report", "commit patterns", "developer efficiency", "developer evaluation", "slacking index", "摸鱼指数", "工作习惯分析", "代码分析", "研发效率", "代码质量", "开发者评估", "developer score".

ClawHub Agent Skills author: KongBai233 v1.0.0 MIT-0 37 files body ≈ 3 235 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 63/100 · Has gaps — weak spots: inputs and preconditions, consistency, running it twice

AnalyzerSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
98/100
safety, quality, tests
Safety 60%
100
Quality 40%
95
Run on models
none yet
Process rating
C
63/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
Running it twice w 4
30
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: 34. 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 63/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 23 mutating operations with no state check
    • 40Consistency. Frontmatter name (code-analysis) differs from the folder (code-analysis-skills-1-0-6)
    • 60Tools and files. Uses tools (git, python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 61 steps
    • 100Failures and branches. 1 branches, has a failure section
    • 100Execution cost. Instruction body is 3235 tokens
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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

    • +4Description does not say when NOT to use the skill (false activations)
    • -225 emoji in the instructions: noise for the model
    • +2Single-language instructions
    • +5Description quotes 10 example trigger phrases
    • +3Description length 580: enough signal without eating the budget
    • +4Structure: 28 headings
    • +3Step-by-step instructions: 61 items
    • +3Output format is stated explicitly
    • +4Has examples (10 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 95.

    External checks

    ClawHub: suspicious
    This skill runs locally, but it ranks and labels individual developers from Git history, so it needs careful review before installation.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026