SKILLEMALL.ai

AD code-reviewer

Thorough code review with focus on security, performance, and best practices for Go projects. Includes Go test coverage analysis (line/function/branch coverage) and reporting. Use when: reviewing Go code, performing security audits, checking for code quality, reviewing pull requests, or when user mentions code review, PR review, security vulnerabilities, performance issues, test coverage.

ClawHub Agent Skills author: jjjypink1211 v1.0.0 MIT-0 10 files body ≈ 1 531 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process D 47/100 · Unfinished process — weak spots: when it triggers, inputs and preconditions, failures and branches

AnalyzerSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
97/100
safety, quality, tests
Safety 60%
100
Quality 40%
92
Run on models
none yet
Process rating
D
47/100
Unfinished process
Inputs and preconditions w 11
0
Failures and branches w 10
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: 10. 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 47/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 1 mutating operations with no state check
    • 40Consistency. Frontmatter name (code-reviewer) differs from the folder (jinyun1)
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 100Steps. 52 steps
    • 100Execution cost. Instruction body is 1531 tokens

    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 391: enough signal without eating the budget
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 52 items
    • +3Output format is stated explicitly
    • +4Has examples (4 code blocks)
    • +4Reference files are cited in the instructions (7 of 8)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.

    External checks

    ClawHub: suspicious
    The skill is mostly a code-review guide, but it also asks for broad team/repository metrics using local repo paths and token-protected PR APIs that go beyond normal Go code review.
    LLM: suspicious (medium) · VirusTotal: · 29 May 2026