SKILLEMALL.ai

AC git-commit-message-generator

Generate conventional commit messages by analyzing staged changes automatically

ClawHub Agent Skills author: Michael Atamuk v1.0.0 MIT-0 4 files body ≈ 3 715 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process C 59/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

AnalyzerSoftware developmentInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
79
Run on models
none yet
Process rating
C
59/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
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: 4. 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 59/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 53 mutating operations with no state check
    • 60Tools and files. Uses tools (bash, git) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 85Steps. 98 steps, 1 vague phrases
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3715 tokens
    • 100Progress reporting. Reports progress
    • low 16 top-level sections: this looks like several domains in one skill

    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)
    • +3Description length 79: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • -213 emoji in the instructions: noise for the model
    • +1No license
    • +2Single-language instructions
    • +4Structure: 55 headings
    • +3Step-by-step instructions: 98 items
    • +4Has examples (37 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.

    External checks

    ClawHub: clean
    This is a straightforward Git commit-message helper that reads staged diffs to suggest a conventional commit message, with no executable code or hidden install behavior found.
    LLM: benign (high) · VirusTotal: · 29 May 2026