SKILLEMALL.ai
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BF wechat-title

基于热门数据生成公众号爆款标题或对用户标题进行多维度评分的专业工具。当用户需要生成公众号标题、查询爆款内容、分析热门趋势、获取创作灵感、参考爆款规律时使用。触发词：公众号标题、爆款标题、标题生成、标题评分、公众号爆款。

ClawHub Agent Skills author: to the moon v1.0.2 MIT-0 5 files body ≈ 1 193 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process F 31/100 · Will not run — References files that are not bundled: 链接

ProcedureGitHubInfrastructuretype 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
85/100
safety, quality, tests
Safety 60%
100
Quality 40%
63
Run on models
none yet
Process rating
F
31/100
Will not run
References files that are not bundled: 链接
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 · 0

✓ No critical or high findings

Files scanned: 5. 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: 链接
  • note frontmatter-key unknown frontmatter key "dependency"

Process rating: all ten parameters 31/100

Will not run. References files that are not bundled: 链接
  • 0Tools and files. 1 referenced file(s) missing: 链接
  • 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
  • 40Consistency. Frontmatter name (wechat-title) differs from the folder (gzh-official-account-title-generator)
  • 100Steps. 43 steps
  • 100Execution cost. Instruction body is 1193 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)
  • +3Description length 109: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -213 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +4Structure: 22 headings
  • +3Step-by-step instructions: 43 items
  • +4Has examples (7 code blocks)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 63.

External checks

ClawHub: suspicious
The skill’s main purpose is coherent, but it has review-worthy risks around broad activation and possible API key exposure in debug logs.
LLM: suspicious (high) · VirusTotal: · 3 Jun 2026