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BF guaikei-douyin-data-funnel

用数字看技能：4 个 CLI 命令、5 类可查数据（视频/图文/用户/评论/热榜）、5 维筛选参数、10000 条单次上限、3 次网络重试。当用户做抖音搜索、竞品分析、舆情监控、热点追踪、爆款选题时使用，输出纯 JSON。

ClawHub Agent Skills author: engheng-art v1.0.0 MIT-0 34 files body ≈ 1 068 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

用数字看技能：4 个 CLI 命令、5 类可查数据（视频/图文/用户/评论/热榜）、5 维筛选参数、10000 条单次上限、3 次网络重试。当用户做抖音搜索、竞品分析、舆情监控、热点追踪、爆款选题时使用，输出纯 JSON。

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

IntegrationInfrastructureMarketingtype 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 1068 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 111: 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
The skill mostly does advertised Douyin data collection, but it needs Review because its triggers are broad, it automatically stores fetched social data locally, and some runtime behavior exceeds its own stated limits.
LLM: suspicious (high) · 25 Aug 2026