SKILLEMALL.ai
RU Sign in

BD Claw Security Scanner

基于Moltbook社区的高度关注（4151点赞的帖子：供应链攻击风险），我们开发了这个技能安全扫描器。

modbender/skill-library-mcp Agent Skills author: modbender MIT 6 files body ≈ 1 456 tokens Open the sourcegithub.com↗ analyzed 2 d ago

基于Moltbook社区的高度关注（4151点赞的帖子：供应链攻击风险），我们开发了这个技能安全扫描器。

As a process D 41/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureSoftware developmentData and analyticstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
81/100
safety, quality, tests
Safety 60%
94
Quality 40%
62
Run on models
none yet
Process rating
D
41/100
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

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 · 6

✓ No critical or high findings

Medium and low: 6
  • low Secrets in code secret-labelled-token test_security_scanner.py:27
    Labelled token / key literal (vendor format unknown — verify it is not a live credential) (placeholder value)
    API_KEY = "sk_t…def"
    placeholder
  • low Secrets in code secret-password-literal test_security_scanner.py:27
    Hard-coded password / key literal (may be an example) (placeholder value)
    API_KEY = "sk_t…def"
    placeholder
  • low Secrets in code secret-aws-key test_security_scanner.py:30
    AWS access key ID (placeholder value)
    AWS_ACCESS_KEY_ID = "AKIA…PLE"
    placeholder
  • low Secrets in code secret-password-literal test_security_scanner.py:66
    Hard-coded password / key literal (may be an example) (test fixture / example file; quoted — discussed, not commanded)
    SECRET_KEY=supe…123
    fixturequoted
  • low Secrets in code secret-labelled-token test_security_scanner.py:100
    Labelled token / key literal (vendor format unknown — verify it is not a live credential) (placeholder value)
    API_KEY = "sk_t…def"
    placeholder
  • low Secrets in code secret-password-literal test_security_scanner.py:100
    Hard-coded password / key literal (may be an example) (placeholder value)
    API_KEY = "sk_t…def"
    placeholder

Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 41/100

  • 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 (Claw Security Scanner) differs from the folder (claw-security-scanner)
  • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
  • 100Steps. 116 steps
  • 100Execution cost. Instruction body is 1456 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)
  • +3Description length 52: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -221 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +4Structure: 57 headings
  • +3Step-by-step instructions: 116 items
  • +4Has examples (12 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 62.