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BC qwen-code

Run Alibaba Cloud Qwen Code CLI via background process for task execution, code review, and automation.

modbender/skill-library-mcp Agent Skills author: modbender MIT 11 files · 2 scripts body ≈ 1 597 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Run Alibaba Cloud Qwen Code CLI via background process for task execution, code review, and automation.

As a process C 62/100 · Has gaps — weak spots: result and completion, consistency, running it twice

ProcedureSoftware developmenttype 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
88/100
safety, quality, tests
Safety 60%
96
Quality 40%
76
Run on models
none yet
Process rating
C
62/100
Has gaps
Result and completion w 14
0
Running it twice w 4
30
Consistency w 8
40
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 · 4

✓ No critical or high findings

Medium and low: 4
  • low Secrets in code secret-high-entropy-token assets/examples/headless-mode.example.js:102
    High-entropy token-like string (may be an id, hash or a credential) (placeholder value)
    function exam…ion() {
    placeholder
  • low Secrets in code secret-high-entropy-token assets/examples/headless-mode.example.js:116
    High-entropy token-like string (may be an id, hash or a credential) (placeholder value)
    function exam…ons() {
    placeholder
  • low Secrets in code secret-high-entropy-token assets/examples/headless-mode.example.js:135
    High-entropy token-like string (may be an id, hash or a credential) (placeholder value)
    // exam…ion();
    placeholder
  • low Secrets in code secret-high-entropy-token assets/examples/headless-mode.example.js:136
    High-entropy token-like string (may be an id, hash or a credential) (placeholder value)
    // exam…ons();
    placeholder

Files scanned: 11. 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 62/100

  • 0Result and completion. Does not say what the result is
  • 30Running it twice. 1 mutating operations with no state check
  • 40Consistency. Frontmatter name (qwen-code) differs from the folder (qwen-code-skill)
  • 50When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 29 steps
  • 100Failures and branches. 1 branches, has a failure section
  • 100Execution cost. Instruction body is 1597 tokens
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 13 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (3 tags): a typed call is more reliable

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 103: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +4Structure: 26 headings
  • +3Step-by-step instructions: 29 items
  • +4Has examples (13 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.