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BF jeffli-wechat-post

微信公众号/朋友圈营销内容智能体。输入产品/服务主题、卖点、讲师信息、配图需求，输出专业文案+结构化配图。触发词：发朋友圈、生成朋友圈文案、微信图文、朋友圈营销、create wechat post、generate wechat image post。

ClawHub Agent Skills author: jeffli2002 v2.1.2 MIT-0 14 files body ≈ 2 326 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process F 36/100 · Will not run — References files that are not bundled: {图片路径}, scripts/kie_create_task.py, scripts/kie_gen_robust.py

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
81/100
safety, quality, tests
Safety 60%
99
Quality 40%
55
Run on models
none yet
Process rating
F
36/100
Will not run
References files that are not bundled: {图片路径}, scripts/kie_create_task.py, scripts/kie_gen_robust.py
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
This is a copy of a skill from another catalog; the rating counts the canonical one: jeffli-wechat-post (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.
  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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Secrets in code secret-high-entropy-token gpt-image-2-prompt-index.md:4
    High-entropy token-like string (may be an id, hash or a credential)
    > 数据来源：awes…pts（483+ curated cases）

Files scanned: 14. 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: {图片路径}
  • warning missing-ref reference to a missing file: scripts/kie_create_task.py
  • warning missing-ref reference to a missing file: scripts/kie_gen_robust.py
  • warning missing-ref reference to a missing file: scripts/kie_callback_server.py
  • warning missing-ref reference to a missing file: scripts/kie_gpt_image2.py

Process rating: all ten parameters 36/100

Will not run. References files that are not bundled: {图片路径}, scripts/kie_create_task.py, scripts/kie_gen_robust.py
  • 0Tools and files. 5 referenced file(s) missing: {图片路径}, scripts/kie_create_task.py, scripts/kie_gen_robust.py
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (jeffli-wechat-post) differs from the folder (wechat-post-gpt-image2)
  • 50Failures and branches. 0 branches, has a failure section
  • 100Steps. 54 steps
  • 100Execution cost. Instruction body is 2326 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)
  • +3Output format is not stated: the model decides each time
  • -240 emoji in the instructions: noise for the model
  • -34 of 6 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 127: enough signal without eating the budget
  • +4Structure: 28 headings
  • +3Step-by-step instructions: 54 items
  • +4Has examples (13 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 55.

External checks

ClawHub: suspicious
The skill mostly matches a WeChat marketing poster generator, but it exposes review-worthy network, credential, and data-retention risks.
LLM: suspicious (high) · VirusTotal: · 29 May 2026