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AC tiktok-home-downloader

TikTok主页视频批量提取 — 输入TikTok主页链接/handle，自动拉取账号主页全部作品并解析无水印下载链接，支持批量一键下载到本地。适用场景：竞品账号内容拆解与逐帧学习、收藏喜欢的创作者全部作品避免被删、批量搬运素材二次剪辑创作、保存自己账号作品做本地备份防丢失、课程/教程类视频离线囤货反复看、甲方要求提供无水印源文件、达人合作前快速拉取对方作品做背调分析。触发词：TikTok主页下载、TikTok视频下载、TikTok批量下载、TikTok无水印下载、下载TikTok作品、TikTok账号视频提取、TikTok主页视频批量提取、TikTok去水印、TikTok视频备份、竞品视频下载。

redfox-data/redfox-community Agent Skills author: redfox-data 5 files body ≈ 1 333 tokens Open the sourcegithub.com↗ analyzed 5 h ago

TikTok主页视频批量提取 —…

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

IntegrationMarketingtype and topics are labelled automatically from the skill text
Runs in: 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) OpenClaw Goose OpenCode
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
79
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: 5. 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 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. 15 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1333 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 302: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 15 items
  • +4Has examples (3 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.