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版本化开发流水线 —— 与 version-manager 和 project-manager 集成的完整开发流程

Blockedguard blocked the skill: signs of malicious behaviour
modbender/skill-library-mcp Agent Skills author: modbender MIT 4 files body ≈ 2 755 tokens Open the sourcegithub.com↗ analyzed 2 d ago

版本化开发流水线 —— 与 version-manager 和 project-manager 集成的完整开发流程

As a process D 45/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureAI and agentstype 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
F
33/100
safety, quality, tests
Safety 60%
10
Quality 40%
68
Run on models
none yet
Process rating
D
45/100
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
Guard blocked this skill: critical findings below. Do not install it until the author fixes them.

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Secrets in code
If you install

The files contain someone else's key or token. If it is live, your agent will call third-party services under a stranger's identity; if it was revoked, the skill's scripts simply fail. Such a key often arrives with the author's whole workspace, personal data included.

For the author

The key is visible to everyone who downloaded the skill and has likely been copied by catalog-scanning bots already. Revoke it now, check bills and access logs, then reissue.

How to improve

  1. Remove the critical guard findings (secrets, dangerous commands, hidden instructions): while they stand the skill is blocked and cannot grade above F.
  2. 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 · 3

  • critical Secrets in code secret-openai-key lib/claude_api.py:13
    OpenAI-style API key (quoted — discussed, not commanded)
    API_KEY = "sk-Z…AuV"
    quoted
Medium and low: 2
  • medium Secrets in code secret-labelled-token lib/claude_api.py:13
    Labelled token / key literal (vendor format unknown — verify it is not a live credential)
    API_KEY = "sk-Z…AuV"
  • low Secrets in code secret-password-literal lib/claude_api.py:13
    Hard-coded password / key literal (may be an example)
    API_KEY = "sk-Z…AuV"

Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 45/100

  • 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
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 10 mutating operations with no state check
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 100Steps. 17 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2755 tokens
  • 100Progress reporting. Reports progress
  • low 10 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)
  • +3Description length 57: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -214 emoji in the instructions: noise for the model
  • +2Single-language instructions
  • +4Structure: 42 headings
  • +3Step-by-step instructions: 17 items
  • +4Has examples (27 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.