SKILLEMALL.ai

AD xiaohongshu-win

小红书内容工具 Windows 原生版。 基于 Node.js + Playwright,直接控制本地 Chromium 浏览器, 无需 WSL、无需 Linux 二进制、无需 Python、无需任何外部服务。 核心功能: - 🔍 内容搜索 - 关键词搜索,分析热度排行 - 📊 话题报告 - 自动生成热点分析 Markdown 报告 - 📝 笔记发布 - 帮你写+帮你发图文笔记 - 🔔 定时任务 - 每天自动搜热点(支持 Cron 定时) - 🖼️ 封面生成 - 集成即梦AI生成封面图片 使用场景: - "搜索小红书上关于XX的内容" - "帮我在小红书发一篇笔记" - "小红书XX话题报告" - "跟踪一下小红书上的XX热点" 适用系统:Windows 10/11 (x64),需要 Node.js 18+

ClawHub Agent Skills author: 多动朕 v1.1.0 MIT-0 7 files body ≈ 594 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedurePlaywrightInfrastructureSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
74
Run on models
none yet
Process rating
D
43/100
Unfinished process
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: 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 43/100

  • 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
  • 30Running it twice. 1 mutating operations with no state check
  • 60Tools and files. Uses tools (node) that frontmatter does not declare
  • 100Steps. 7 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 594 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
  • -31 of 3 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 4 example trigger phrases
  • +3Description length 366: enough signal without eating the budget
  • +4Structure: 9 headings
  • +3Step-by-step instructions: 7 items
  • +4Has examples (4 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.

External checks

ClawHub: suspicious
This is a coherent Xiaohongshu automation tool, but it can reuse saved login sessions and publish to a real account without a final confirmation step.
LLM: suspicious (high) · VirusTotal: · 29 May 2026