SKILLEMALL.ai

BC xiaohongshu-data-research

小红书数据智能助手。自媒体从业者的数据获取工具,提供小红书搜索、作品获取、实时评论数据等实时数据的批量获取,为后续的内容研究、选题分析、用户痛点、数据分析、市场调研、对标账号监控、舆情分析、小红书增长等场景提供真实可靠的数据支撑。支持四大能力:(1) 关键词搜索笔记/视频,可按点赞数、评论数、收藏数、发布时间、内容类型筛选排序;(2) 博主作品抓取,按主页链接获取博主的互动数据(粉丝量、点赞量或收藏量等)或公开作品列表;(3) 笔记(视频)详情,获取详情数据及互动数据等,分析笔记的市场表现;(4) 笔记评论分析,按笔记链接获取评论内容与互动数据。用户提到小红书/xhs/rednote 且需要查数据、市场调研、舆情监测、做选题、竞品监控、KOL筛选、舆情分析时调用;无需登录账号

ClawHub Agent Skills author: why20261 v1.1.4 MIT-0 25 files · 18 scripts body ≈ 2 260 tokens Open the sourceclawhub.ai↗ analyzed 7 d ago

小红书数据智能助手。自媒体从业者的数据获取工具,提供小红书搜索、作品获取、实时评论数据等实时数据的批量获取,为后续的内容研究、选题分析、用户痛点、数据分析、市场调研、对标账号监控、舆情分析、小红书增长等场景提供真实可靠的数据支撑。支持四大能力:(1)…

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

ProcedureAI and agentsWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
74
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: 25. 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 "homepage"

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. 40 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2260 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
  • -229 emoji in the instructions: noise for the model
  • +2Single-language instructions
  • +3Description length 342: enough signal without eating the budget
  • +4Structure: 20 headings
  • +3Step-by-step instructions: 40 items
  • +4Has examples (4 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)
  • +1License stated

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

External checks

ClawHub: clean
The skill is a disclosed Xiaohongshu public-data CLI that uses a GUAIKEI API token, sends user-provided keywords or links to guaikei.com, and saves returned results locally.
LLM: benign (high) · VirusTotal: · 29 Sept 2026