SKILLEMALL.ai

AD guaikei-xiaohongshu-search-detail-comment-post

采集小红书公开内容数据:关键词搜索笔记、查看笔记详情、拉取笔记评论、监控博主作品列表,输出结构化JSON,用于爆款挖掘、竞品分析、KOL筛选、评论舆情与趋势洞察。当用户想找小红书高赞内容、分析某篇笔记或其评论区、追踪某个博主的发文动态、做小红书选题调研或市场趋势分析时调用——即使用户没直接说"搜小红书",只要意图涉及小红书内容数据获取就应触发。支持图文/视频筛选、点赞/评论/收藏排序、发布时间限定,单次最多返回1万条,可直接衔接选题汇总、高赞对比、评论观点聚类、发文节奏分析等后续任务。

ClawHub Agent Skills author: engheng-art v1.0.0 MIT-0 24 files body ≈ 1 104 tokens Open the sourceclawhub.ai analyzed 3 d ago

采集小红书公开内容数据:关键词搜索笔记、查看笔记详情、拉取笔记评论、监控博主作品列表,输出结构化JSON,用于爆款挖掘、竞品分析、KOL筛选、评论舆情与趋势洞察。当用户想找小红书高赞内容、分析某篇笔记或其评论区、追踪某个博主的发文动态、做小红书选题调研或市场趋势分析时调用——即使用户没直接说"搜小红书",只要意图涉及…

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
77
Run on models
none yet
Process rating
D
46/100
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: 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")

Process rating: all ten parameters 46/100

  • 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
  • 60Tools and files. Uses tools (node) that frontmatter does not declare
  • 100Steps. 17 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1104 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 245: enough signal without eating the budget
  • +4Structure: 10 headings
  • +3Step-by-step instructions: 17 items
  • +4Has examples (5 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: 77.

External checks

ClawHub: clean
This skill coherently provides Xiaohongshu public-content data retrieval through a disclosed third-party API, with notable but disclosed token, network, and local logging behavior.
LLM: benign (high) · VirusTotal: · 16 Aug 2026