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BF wechat-oa

WeChat Official Account draft management toolkit. Trigger words: 看看草稿箱/查看草稿/草稿列表/公众号草稿/创建草稿/新建草稿/发文章到公众号/推送文章/更新草稿/删除草稿/生成封面图/上传图片. Official API.

ClawHub Agent Skills author: Woody v3.0.3 MIT-0 31 files body ≈ 1 680 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process F 33/100 · Will not run — References files that are not bundled: path, images/photo.jpg

GeneratorInfrastructuretype 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
83/100
safety, quality, tests
Safety 60%
100
Quality 40%
57
Run on models
none yet
Process rating
F
33/100
Will not run
References files that are not bundled: path, images/photo.jpg
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
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: 31. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 6, column 14: description: WeChat Official Account draft management toolkit. Trigger words: 看… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
  • warning missing-ref reference to a missing file: path
  • warning missing-ref reference to a missing file: images/photo.jpg
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "displayName"
  • note frontmatter-key unknown frontmatter key "summary"
  • note frontmatter-key unknown frontmatter key "description_zh"
  • note frontmatter-key unknown frontmatter key "email"
  • note frontmatter-key unknown frontmatter key "wechat_mp"
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 33/100

Will not run. References files that are not bundled: path, images/photo.jpg
  • 0Tools and files. 2 referenced file(s) missing: path, images/photo.jpg
  • 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. 11 mutating operations with no state check
  • 100Steps. 41 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1680 tokens
  • low 12 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (11 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)
  • +3Output format is not stated: the model decides each time
  • -222 emoji in the instructions: noise for the model
  • -41 reference files, but SKILL.md never points to them: the model will not open them
  • +2Single-language instructions
  • +3Description length 145: enough signal without eating the budget
  • +4Structure: 29 headings
  • +3Step-by-step instructions: 41 items
  • +4Has examples (7 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 57.

External checks

ClawHub: suspicious
This WeChat publishing skill does what it claims, but it can hand long-lived account secrets and draft content to a relay service and perform deletions without enough safeguards.
LLM: suspicious (high) · 12 Jul 2026