SKILLEMALL.ai

AD wangyin-zhongnian-self-media

网瘾中年的自媒体技能——微信公众号「网瘾中年」专用内容生产与发布全流程。覆盖选题评估、创作简报、爆款公式匹配、公众号原生写作、去AI味精修、AIGC合规守门、封面生成、草稿箱推送、数据复盘九个环节。触发词:"写一篇公众号""发一篇""推草稿箱""推送草稿""做选题""软广""日报排版""复盘阅读数据""爆款公式""网瘾中年"。不用于X/小红书/抖音等其他平台创作,不用于纯代码任务,不用于视频号发布(走独立视频自动化)。

ClawHub Agent Skills author: Eric v1.1.0 MIT-0 7 files body ≈ 1 573 tokens Open the sourceclawhub.ai analyzed 2 d ago

网瘾中年的自媒体技能——微信公众号「网瘾中年」专用内容生产与发布全流程。覆盖选题评估、创作简报、爆款公式匹配、公众号原生写作、去AI味精修、AIGC合规守门、封面生成、草稿箱推送、数据复盘九个环节。触发词:"写一篇公众号""发一篇""推草稿箱""推送草稿""做选题""软广""日报排版""复盘阅读数据""爆款公式""网…

As a process D 48/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureSoftware developmentAI and agentsSecuritytype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
75
Run on models
none yet
Process rating
D
48/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
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: 7. 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")

Process rating: all ten parameters 48/100

  • 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
  • 30Running it twice. 1 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 100Steps. 34 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1573 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
  • -4Absolute local paths (C:\Users, /home/…): not portable
  • -216 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 2 example trigger phrases
  • +3Description length 211: enough signal without eating the budget
  • +4Structure: 15 headings
  • +3Step-by-step instructions: 34 items
  • +4Has examples (2 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.

External checks

ClawHub: clean
This skill is a disclosed single-account WeChat content workflow with draft-box publishing safeguards, though users should understand it can read local workflow files and run publishing-related commands when asked.
LLM: benign (high) · VirusTotal: · 27 Jul 2026