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搜索和读取微信公众号文章的完整工具，支持关键词搜索与全文提取。 **只要用户提到以下任何场景，必须使用此 skill：** (1) 搜索公众号文章、按关键词查找微信内容 (2) 读取、摘要、分析、翻译 mp.weixin.qq.com 链接的内容 (3) 用户说"帮我找公众号文章"、"读这篇微信文章"、"搜索公众号"、"抓取公众号" (4) 用户粘贴了微信文章 URL 并要求提取或处理内容 (5) 需要从微信生态获取资讯、报告、行业信息 即使用户没有明确说"微信"，只要涉及公众号内容获取或提取，也应触发此 skill。 Triggers: 搜索公众号, 微信文章, 读这篇公众号, 抓取公众号, wechat article, mp.weixin.qq.com, 公众号内容, 微信链接

ClawHub Agent Skills author: onlyloveher v1.0.0 MIT-0 9 files body ≈ 548 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 39/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureWriting and documentsInfrastructuretype 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
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
74
Run on models
none yet
Process rating
D
39/100
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
This is a copy of a skill from another catalog; the rating counts the canonical one: wechat-articles (ClawHub)

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 · 0

✓ No critical or high findings

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")
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 39/100

  • 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
  • 30Running it twice. 1 mutating operations with no state check
  • 40Consistency. Frontmatter name (wechat-articles) differs from the folder (wechat-articles-cn)
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 7 steps
  • 100Execution cost. Instruction body is 548 tokens

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

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -33 of 5 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +5Description quotes 3 example trigger phrases
  • +3Description length 346: enough signal without eating the budget
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 7 items
  • +4Has examples (6 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.

External checks

ClawHub: clean
This is a disclosed WeChat public-account article search and reader, with normal web-fetching and dependency risks but no evidence of hidden, destructive, or credential-stealing behavior.
LLM: benign (medium) · VirusTotal: · 29 May 2026