SKILLEMALL.ai

BC Privacy Policy Generator

Privacy Policy Generator - 隐私政策生成器. Use when you need privacy policy capabilities. Triggers on: privacy policy.

ClawHub Agent Skills author: bytesagain-lab v2.0.1 MIT-0 5 files · 2 scripts body ≈ 231 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 55/100 · Has gaps — weak spots: result and completion, failures and branches, consistency

GeneratorLegaltype and topics are labelled automatically from the skill text
JSON
Technical rating
B
84/100
safety, quality, tests
Safety 60%
100
Quality 40%
61
Run on models
none yet
Process rating
C
55/100
Has gaps
Result and completion w 14
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: 5. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: All mapping items must start at the same column at line 4, column 1: description: "Privacy Policy Generator - 隐私政策生成器. Use when you need privacy pol… 隐私政策生成器。GDPR/CCPA合规、App/网站隐私政策、合规审计。Privacy policy generator with GDPR, CCPA … ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
    • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
    • note frontmatter-key unknown frontmatter key "homepage"
    • note frontmatter-key unknown frontmatter key "source"

    Process rating: all ten parameters 55/100

    • 0Result and completion. Does not say what the result is
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 40Consistency. Frontmatter name (Privacy Policy Generator) differs from the folder (privacy-policy)
    • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 7 steps
    • 100Execution cost. Instruction body is 231 tokens
    • 100Running it twice. No mutating operations
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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)
    • +3Description length 111: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • -32 of 2 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +4Structure: 6 headings
    • +3Step-by-step instructions: 7 items
    • +4Has examples (1 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 61.

    External checks

    ClawHub: suspicious
    This appears to be a privacy-policy generator, but it also bundles an unrelated security-tool script that gives misleading results and stores user inputs locally.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026