SKILLEMALL.ai

AD skill-security-check

Skill 发布前安全检查工具。在发布 skill 到 ClawHub 前,自动扫描敏感信息(API Key、Token、私钥、邮箱、手机号、精确坐标等)。Use before publishing any skill to prevent leaking private data.

ClawHub Agent Skills author: vlalamoon v1.0.0 MIT-0 3 files · 1 script body ≈ 407 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
98
Quality 40%
84
Run on models
none yet
Process rating
D
49/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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 · 2

    ✓ No critical or high findings

    Medium and low: 2
    • low Secrets in code secret-password-literal SKILL.md:51
      Hard-coded password / key literal (may be an example) (placeholder value)
      ./my-skill/script.py:api_key = "sk-a…..."
      placeholder
    • low Secrets in code secret-password-literal SKILL.md:76
      Hard-coded password / key literal (may be an example) (placeholder value)
      API_KEY = "sk-a…..."
      placeholder

    Files scanned: 3. 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 49/100

    • 0Result and completion. Does not say what the result is
    • 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
    • 40Consistency. Frontmatter name (skill-security-check) differs from the folder (pre-publish-security-check)
    • 100Tools and files. No external tools needed
    • 100Steps. 5 steps
    • 100Execution cost. Instruction body is 407 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)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 142: enough signal without eating the budget
    • +4Structure: 13 headings
    • +3Step-by-step instructions: 5 items
    • +4Has examples (7 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

    External checks

    ClawHub: clean
    This is a local pre-publish checker that scans a user-chosen skill folder for possible secrets, with no evidence of hidden networking, persistence, or destructive behavior.
    LLM: benign (high) · VirusTotal: · 29 May 2026