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AI科普视频全流程自动化制作技能。将数字人形象（Google Flow / SadTalker）、AI语音克隆（F5-TTS MLX）、Pillow内容幻灯片、逐字卡拉OK字幕（Pillow + FFmpeg）、以及专业级音视频QA整合为8阶段自动化流水线。覆盖：脚本策划 → 数字人生成 → TTS语音克隆 → 幻灯片渲染 → 字幕渲染 → 音频修复 → 最终合成（FFmpeg xfade + acrossfade + alimiter）→ 专业QA审查。触发词：AI科普视频、制作科普视频、做个AI讲解视频、生成科技短视频。**推荐硬件：Mac mini M系列 16GB内存**，利用Apple Silicon MLX加速语音克隆和本地渲染。

ClawHub Agent Skills author: 寒武纪智能Cambrian Intelligence v1.0.0 MIT-0 9 files body ≈ 3 647 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

AI科普视频全流程自动化制作技能。将数字人形象（Google Flow / SadTalker）、AI语音克隆（F5-TTS MLX）、Pillow内容幻灯片、逐字卡拉OK字幕（Pillow + FFmpeg）、以及专业级音视频QA整合为8阶段自动化流水线。覆盖：脚本策划 → 数字人生成 → TTS语音克隆 →…

As a process F 47/100 · Will not run — References files that are not bundled: scripts/fix_sadtalker_numpy.py

ProcedureMedia and videotype 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
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
88
Run on models
none yet
Process rating
F
47/100
Will not run
References files that are not bundled: scripts/fix_sadtalker_numpy.py
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. 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: 9. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: scripts/fix_sadtalker_numpy.py
  • note frontmatter-key unknown frontmatter key "agent_created"

Process rating: all ten parameters 47/100

Will not run. References files that are not bundled: scripts/fix_sadtalker_numpy.py
  • 0Tools and files. 1 referenced file(s) missing: scripts/fix_sadtalker_numpy.py
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 4 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 100Steps. 56 steps
  • 100When it triggers. States when to use and when not to
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3647 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
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +3Description length 325: enough signal without eating the budget
  • +4Structure: 22 headings
  • +3Step-by-step instructions: 56 items
  • +4Has examples (12 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)
  • +3All 4 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.

External checks

ClawHub: suspicious
This video-production skill is mostly coherent, but it asks agents to use authenticated browser sessions, biometric face and voice inputs, and runtime package installation without enough scoping or user safeguards.
LLM: suspicious (high) · 3 Jul 2026