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AC xhs-insight-guaikei

搜索/查看/抓取小红书公开笔记、评论与博主作品，返回结构化数据。当用户提到小红书、红笔记、xhs、rednote，或给出 xiaohongshu.com/xhslink.com 链接，且想了解内容、找爆款、分析竞品、筛 KOL、看评论、追趋势、做选题、准备报告时使用本技能；即使用户没明确说"小红书"或"数据"，只要语境是社媒内容调研也适用。不用于登录、发布或其他平台。

ClawHub Agent Skills author: engheng-art v1.0.0 MIT-0 24 files body ≈ 988 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

搜索/查看/抓取小红书公开笔记、评论与博主作品，返回结构化数据。当用户提到小红书、红笔记、xhs、rednote，或给出 xiaohongshu.com/xhslink.com 链接，且想了解内容、找爆款、分析竞品、筛…

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureWriting and documentstype 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
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
Run on models
none yet
Process rating
C
53/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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: 24. 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")
  • note frontmatter-key unknown frontmatter key "name_cn"

Process rating: all ten parameters 53/100

  • 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
  • 100Tools and files. No external tools needed
  • 100Steps. 19 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 988 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
  • +2Single-language instructions
  • +3Description length 185: enough signal without eating the budget
  • +4Structure: 14 headings
  • +3Step-by-step instructions: 19 items
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.

External checks

ClawHub: clean
This skill is a disclosed Xiaohongshu public-data research tool that uses a Guaikei API token, sends queries and links to Guaikei, and saves results locally.
LLM: benign (high) · VirusTotal: · 13 Aug 2026