AD video-to-notes
将视频内容（课程/讲座/教程/纪录片/会议/演讲等）自动转为高质量结构化学习笔记。核心价值：看视频容易忘、看一遍记不住 → 转成笔记随时回看。支持本地视频文件、YouTube/B站等网络链接。流程：提取音轨 → Whisper 语音转文字 → AI 生成结构化笔记。适用场景：任何想从视频中高效学习的人——自学程序员、学生、职场进修者、知识爱好者。触发条件：用户提供视频路径/链接，或说"把这个视频整理成笔记"、"帮我记笔记"、"转成学习笔记"。支持中英文，一次 1-3 个文件。
As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
ProcedureYouTubeMedia and videoInfrastructuretype and topics are labelled automatically from the skill text
How to improve
- 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: 7. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 46/100
- 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
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 19 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1414 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -216 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +5Description quotes 2 example trigger phrases
- +3Description length 240: enough signal without eating the budget
- +4Structure: 18 headings
- +3Step-by-step instructions: 19 items
- +4Has examples (10 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
- +3All 2 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.
External checks
ClawHub: clean
This appears to be a video-to-notes helper whose media processing and file output are expected for its purpose, with no evidence of theft, deception, or destructive behavior.
LLM: benign (medium) · VirusTotal: · 9 Jul 2026