SKILLEMALL.ai

AC improvement-gate

当执行完变更需要验证是否应保留、候选被标记 pending 需要人工审批、或想查看待审队列时使用。6 层机械门禁: Schema→Compile→Lint→Regression→Review→HumanReview,其中 Schema/Compile/Regression/Review 为阻塞层(失败即拒绝),Lint 和 HumanReview 为建议层(失败不阻塞但记录警告)。不用于打分(用 improvement-discriminator)或执行变更(用 improvement-executor)。

ClawHub Agent Skills author: _silhouette v1.1.1 MIT-0 7 files body ≈ 1 355 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 60/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, progress reporting

AnalyzerSoftware developmentData and analyticsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
90
Run on models
none yet
Process rating
C
60/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
20
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: 5. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "triggers"

    Process rating: all ten parameters 60/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 100Steps. 28 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1355 tokens
    • 100Running it twice. No mutating operations

    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)
    • +2Single-language instructions
    • +3Description length 256: enough signal without eating the budget
    • +4Structure: 8 headings
    • +3Step-by-step instructions: 28 items
    • +3Output format is stated explicitly
    • +4Has examples (3 code blocks)
    • +3All 2 scripts are documented
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.

    External checks

    ClawHub: suspicious
    The skill mostly fits a quality-gate workflow, but it has under-disclosed authority to modify local files during rollback and uses broad triggers that could activate it outside that workflow.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026