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抖音账号订阅追踪 — 通过抖音号订阅账号（最多20个），Agent 每日 9:00 自动拉取并生成 HTML 报告。账号 ID 直接内置于自动化命令中，无需文件存储。支持多抖音号批量订阅，自动生成精美 HTML 作品报告，终端/Markdown 表格按账号依次展示作品标题、收藏、评论、分享、点赞、发布时间等数据。当用户订阅抖音账号、追踪抖音作品更新、监控抖音竞品账号时使用。触发词：抖音订阅、抖音账号订阅、抖音订阅追踪、抖音作品订阅、抖音账号监控、抖音作品追踪、抖音每日推送、抖音日报。

ClawHub Agent Skills author: RedFox v1.0.2 MIT-0 6 files body ≈ 1 870 tokens Open the sourceclawhub.ai↗ analyzed 29 h ago

抖音账号订阅追踪 — 通过抖音号订阅账号（最多20个），Agent 每日 9:00 自动拉取并生成 HTML 报告。账号 ID 直接内置于自动化命令中，无需文件存储。支持多抖音号批量订阅，自动生成精美 HTML 作品报告，终端/Markdown…

As a process F 33/100 · Will not run — References files that are not bundled: workUrl

IntegrationData and analyticstype 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
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
66
Run on models
none yet
Process rating
F
33/100
Will not run
References files that are not bundled: workUrl
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: 6. 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: workUrl
  • note frontmatter-key unknown frontmatter key "display_name"
  • note frontmatter-key unknown frontmatter key "display_name_en"
  • note frontmatter-key unknown frontmatter key "description_zh"
  • note frontmatter-key unknown frontmatter key "description_en"

Process rating: all ten parameters 33/100

Will not run. References files that are not bundled: workUrl
  • 0Tools and files. 1 referenced file(s) missing: workUrl
  • 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
  • 100Steps. 52 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1870 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

  • +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
  • +1No license
  • +2Single-language instructions
  • +3Description length 244: enough signal without eating the budget
  • +4Structure: 31 headings
  • +3Step-by-step instructions: 52 items
  • +4Has examples (9 code blocks)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.

External checks

ClawHub: suspicious
The skill mostly does what it says, but it under-discloses persistent local storage and silent daily monitoring changes.
LLM: suspicious (high) · 29 Jul 2026