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用户问抖音相关数据问题时用：搜视频、找博主、看评论、查热搜，四类问题对应四个命令。支持"近一周""点赞最多""只要图文"这类口语筛选条件自动转参数。不用于发布/剪辑/下载/代运营，其他平台另寻工具。

ClawHub Agent Skills author: engheng-art v1.0.0 MIT-0 34 files body ≈ 1 071 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

用户问抖音相关数据问题时用：搜视频、找博主、看评论、查热搜，四类问题对应四个命令。支持"近一周""点赞最多""只要图文"这类口语筛选条件自动转参数。不用于发布/剪辑/下载/代运营，其他平台另寻工具。

As a process F 35/100 · Will not run — References files that are not bundled: assets/*.schema.json

ProcedureInfrastructuretype 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
87/100
safety, quality, tests
Safety 60%
100
Quality 40%
67
Run on models
none yet
Process rating
F
35/100
Will not run
References files that are not bundled: assets/*.schema.json
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

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 · 0

✓ No critical or high findings

Files scanned: 34. 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: assets/*.schema.json
  • note frontmatter-key unknown frontmatter key "title"

Process rating: all ten parameters 35/100

Will not run. References files that are not bundled: assets/*.schema.json
  • 0Tools and files. 1 referenced file(s) missing: assets/*.schema.json
  • 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. 31 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1071 tokens
  • 100Running it twice. No mutating operations
  • low 11 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)
  • +3Description length 99: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +4Structure: 13 headings
  • +3Step-by-step instructions: 31 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: 67.

External checks

ClawHub: suspicious
This Douyin research skill is not malicious, but it needs review because it can trigger too broadly, sends its API token in URL parameters, and saves fetched data locally.
LLM: suspicious (high) · 25 Aug 2026