SKILLEMALL.ai

AC fec-validation-fix

Use when running existing project validation commands and fixing failures after code changes, including lint, type-check, unit/integration test, build, CI, or local script failures. Do not use when the task is to design or author new component/E2E tests; Chinese triggers include 验证, 检查失败, 修复失败, CI 失败.

ClawHub Agent Skills author: Bovin Phang v2.6.0 MIT-0 6 files body ≈ 228 tokens Open the sourceclawhub.ai analyzed 24 h ago

Use when running existing project validation commands and fixing failures after code changes, including lint, type-check, unit/integration test, build, CI, or…

As a process C 55/100 · Has gaps — weak spots: result and completion, inputs and preconditions, progress reporting

AnalyzerSoftware developmentData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
88
Run on models
none yet
Process rating
C
55/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
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: 6. 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 55/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 50When it triggers. No condition that starts the skill
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (node) that frontmatter does not declare
    • 100Steps. 25 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 228 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
    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 302: enough signal without eating the budget
    • +4Structure: 7 headings
    • +3Step-by-step instructions: 25 items
    • +4Reference files are cited in the instructions (1 of 1)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.

    External checks

    ClawHub: clean
    This appears to be a project validation and failure-fixing helper with broad activation wording but no evidence of hidden, destructive, or credential-seeking behavior.
    LLM: benign (medium) · VirusTotal: · 7 Jun 2026