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AF wechat-group-operator

WeChat group operations automation for Windows desktop WeChat. Use when the user wants to run recurring group engagement workflows such as morning questions, afternoon follow-ups, and evening case posts in specified微信群, with content pools, posting history, and OpenClaw cron scheduling. Best for群运营、私域活跃、课程群维护、社群节奏 automation. Not for朋友圈 scraping or broad WeChat data extraction.

ClawHub Agent Skills author: Koi v0.1.0 MIT-0 10 files body ≈ 496 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process F 42/100 · Will not run — References files that are not bundled: assets/post_history.json

ProcedureInfrastructuretype 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
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
89
Run on models
none yet
Process rating
F
42/100
Will not run
References files that are not bundled: assets/post_history.json
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: 10. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: assets/post_history.json

Process rating: all ten parameters 42/100

Will not run. References files that are not bundled: assets/post_history.json
  • 0Tools and files. 1 referenced file(s) missing: assets/post_history.json
  • 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
  • 30Running it twice. 4 mutating operations with no state check
  • 100Steps. 33 steps
  • 100When it triggers. States when to use and when not to
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 496 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

  • +5Description has no quoted example phrases that should trigger the skill
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +3Description length 379: enough signal without eating the budget
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 33 items
  • +4Has examples (2 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.

External checks

ClawHub: suspicious
This skill is clearly meant to automate WeChat group posts, but it can send real scheduled messages through an external unreviewed sender with limited safeguards.
LLM: suspicious (high) · VirusTotal: · 29 May 2026