SKILLEMALL.ai

AB skill-vetter-v2

Verification-guided review workflow for inspecting skill packages before use or publication. Classifies risk and flags claims that exceed evidence. Does not itself perform cryptographic verification, emit receipts, or prove a skill is safe.

ClawHub Agent Skills author: nutstrut v0.0.6 MIT-0 13 files · 2 scripts body ≈ 2 592 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 65/100 · Nearly there — weak spots: when it triggers, running it twice, progress reporting

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
97
Quality 40%
80
Run on models
none yet
Process rating
B
65/100
Nearly there
Progress reporting w 2
0
When it triggers w 12
20
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 · 3

    ✓ No critical or high findings

    Medium and low: 3
    • low Risky intent intent-offensive-security assets/REVIEW-CHECKLIST.md:23
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      - privilege escalation
    • low Dangerous commands cmd-privilege scripts/scan-skill.sh:37
      Privilege escalation / world-writable permissions (string literal in code, not executed; documentation of a security skill)
      [privilege]='sudo|chmod 777|chown '
      code literalsecurity skill
    • low Risky intent intent-offensive-security SKILL.md:146
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      * privilege escalation or system-level modification

    Files scanned: 13. 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 65/100

    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 3 mutating operations with no state check
    • 55Failures and branches. 1 branches
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 74 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2592 tokens
    • 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)
    • -42 reference files, but SKILL.md never points to them: the model will not open them
    • -31 of 2 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +3Description length 240: enough signal without eating the budget
    • +4Structure: 25 headings
    • +3Step-by-step instructions: 74 items
    • +3Output format is stated explicitly
    • +4Has examples (6 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.

    External checks

    ClawHub: clean
    This skill is a disclosed local review workflow with an optional reminder hook and no evidence of hidden network, credential, destructive, or privilege-seeking behavior.
    LLM: benign (high) · VirusTotal: · 9 Jul 2026