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BD WeChat Article Scraper

微信公众号文章抓取工具。从 mp.weixin.qq.com 抓取公开文章（文字+图片+视频），解析内容块顺序，下载图片，按原顺序写入飞书知识库。

ClawHub Agent Skills author: mengzi53 v2.0.0 MIT-0 5 files body ≈ 416 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ReferenceWriting 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
B
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
64
Run on models
none yet
Process rating
D
49/100
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 · 0

✓ No critical or high findings

Files scanned: 5. 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")
  • note frontmatter-key unknown frontmatter key "identifier"
  • note frontmatter-key unknown frontmatter key "emoji"
  • note frontmatter-key unknown frontmatter key "requires"
  • note frontmatter-key unknown frontmatter key "primaryEnv"

Process rating: all ten parameters 49/100

  • 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 Article Scraper) differs from the folder (xiaofei-ziyong-wechat-article-scraper)
  • 100Tools and files. No external tools needed
  • 100Steps. 16 steps
  • 100Execution cost. Instruction body is 416 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 73: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +4Structure: 10 headings
  • +3Step-by-step instructions: 16 items
  • +4Has examples (4 code blocks)
  • +3All 2 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.

External checks

ClawHub: suspicious
This is a disclosed WeChat scraping/import helper, but it uses anti-bot browser evasion and weak URL scoping, so users should review it before installing.
LLM: suspicious (high) · VirusTotal: · 29 May 2026