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BD wechat-mp-reader

直接读取微信公众号文章正文的可执行 skill。适用于用户提供 mp.weixin.qq.com 链接，并明确要你读正文、摘录内容、提取标题、做总结的场景。与很多只给方法或提示词的同类 skill 不同，这个 skill 自带 setup、run 和 Playwright 提取脚本，已经在真实文章上验证能读出标题和正文，不是停留在思路层。

ClawHub Agent Skills author: 文武贝 v0.1.2 MIT-0 9 files · 2 scripts body ≈ 442 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

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

ReferencePlaywrightInfrastructuretype 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
86/100
safety, quality, tests
Safety 60%
99
Quality 40%
67
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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Secrets in code secret-high-entropy-token package-lock.json:17
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…uWm+fFRcIOgKBMiOBP+eXiy…9ab+DDKA==",
    detector

Files scanned: 9. 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 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 (wechat-mp-reader) differs from the folder (shrimp-wechat-mp-reader)
  • 60Tools and files. Uses tools (bash, node) that frontmatter does not declare
  • 100Steps. 56 steps
  • 100Execution cost. Instruction body is 442 tokens
  • 100Running it twice. No mutating operations
  • low 14 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)
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • -4Absolute local paths (C:\Users, /home/…): not portable
  • +1No license
  • +2Single-language instructions
  • +3Description length 170: enough signal without eating the budget
  • +4Structure: 15 headings
  • +3Step-by-step instructions: 56 items
  • +3All 2 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.

External checks

ClawHub: clean
This skill behaves like a disclosed WeChat article reader, with ordinary npm and Playwright setup risks but no evidence of hidden data access or harmful behavior.
LLM: benign (high) · VirusTotal: · 29 May 2026