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BF yaniw-wechat-publisher

用于管理多个微信公众号的内容创作和发布。当用户提到"公众号发布"、"写公众号文章"、"给某个公众号发文"、"切换公众号"、"查看公众号发布情况"、"微信发文"或需要为公众号生成内容、封面图、发布文章时,自动触发此技能。支持多账号管理、内容生成、封面设计、自动发布等完整流程。

ClawHub Agent Skills author: zgedu-new v1.1.0 MIT-0 27 files body ≈ 858 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process F 33/100 · Will not run — References files that are not bundled: references/my_accounts.json, references/config.json, references/multi_account_config.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
B
84/100
safety, quality, tests
Safety 60%
96
Quality 40%
66
Run on models
none yet
Process rating
F
33/100
Will not run
References files that are not bundled: references/my_accounts.json, references/config.json, references/multi_account_config.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. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. 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 · 4

✓ No critical or high findings

Medium and low: 4
  • low Exfiltration read-dotenv 版本更新说明-v1.1.0.md:21
    Reads a .env file
    cp .env.example .env
  • low Exfiltration read-dotenv 版本更新说明-v1.1.0.md:108
    Reads a .env file
    cp .env.example .env
  • low Exfiltration read-dotenv 版本更新说明-v1.1.0.md:130
    Reads a .env file
    cp .env.example .env
  • low Exfiltration read-dotenv README.md:35
    Reads a .env file
    cp .env.example .env

Files scanned: 27. 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")
  • warning missing-ref reference to a missing file: references/my_accounts.json
  • warning missing-ref reference to a missing file: references/config.json
  • warning missing-ref reference to a missing file: references/multi_account_config.json

Process rating: all ten parameters 33/100

Will not run. References files that are not bundled: references/my_accounts.json, references/config.json, references/multi_account_config.json
  • 0Tools and files. 3 referenced file(s) missing: references/my_accounts.json, references/config.json, references/multi_account_config.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
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 1 mutating operations with no state check
  • 100Steps. 85 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 858 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
  • -31 of 8 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 3 example trigger phrases
  • +3Description length 137: enough signal without eating the budget
  • +4Structure: 21 headings
  • +3Step-by-step instructions: 85 items
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.

External checks

ClawHub: suspicious
This is a disclosed WeChat publishing helper, but it can use account credentials and create WeChat drafts from broad prompts, so it needs careful review before installation.
LLM: suspicious (high) · VirusTotal: · 29 May 2026