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小红书爆款内容创作专家。一个 Skill 覆盖笔记生成、文案改写、爆款标题生成与评分、封面设计、违禁词检测五大能力，基于红狐数据每日更新的爆款笔记库，把灵感打磨成可直接发布的成品。当用户需要写小红书笔记、改写文案为小红书风格、起标题或评估标题、设计封面、检测违禁词时使用。触发词：小红书笔记、小红书改写、小红书标题、小红书封面、小红书违禁词、小红书创作、小红书爆款。

ClawHub Agent Skills author: to the moon v1.0.0 MIT-0 15 files body ≈ 2 694 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

小红书爆款内容创作专家。一个 Skill…

As a process F 35/100 · Will not run — References files that are not bundled: noteLink, authorLink, ...

IntegrationPlaywrightWordAI and agentstype 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%
98
Quality 40%
64
Run on models
none yet
Process rating
F
35/100
Will not run
References files that are not bundled: noteLink, authorLink, ...
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

The same skill appears in 1 more place: 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 · 2

✓ No critical or high findings

Medium and low: 2
  • low Secrets in code secret-password-literal scripts/fetch_xhs_trends.py:66
    Hard-coded password / key literal (may be an example)
    api_key = match.group(1)
  • low Dangerous commands cmd-shell-rc SKILL.md:73
    Writes to a shell startup file (quoted — discussed, not commanded)
    - macOS/Linux（zsh）：`echo 'export REDFOX_API_KEY=ak_xxx' >> ~/.zshrc && source ~/.zshrc`
    quoted

Files scanned: 15. 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: noteLink
  • warning missing-ref reference to a missing file: authorLink
  • warning missing-ref reference to a missing file: ...
  • note frontmatter-key unknown frontmatter key "dependency"

Process rating: all ten parameters 35/100

Will not run. References files that are not bundled: noteLink, authorLink, ...
  • 0Tools and files. 3 referenced file(s) missing: noteLink, authorLink, ...
  • 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
  • 100Steps. 77 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2694 tokens
  • 100Running it twice. No mutating operations
  • low 12 top-level sections: this looks like several domains in one skill

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
  • -213 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 183: enough signal without eating the budget
  • +4Structure: 41 headings
  • +3Step-by-step instructions: 77 items
  • +4Has examples (9 code blocks)
  • +4Reference files are cited in the instructions (5 of 5)
  • +3All 5 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.

External checks

ClawHub: clean
This skill is a coherent Xiaohongshu content assistant, but users should understand that several features rely on RedFox network services and may process user text, files, URLs, or public post metadata externally.
LLM: benign (high) · VirusTotal: · 4 Sept 2026