AD ai-video-pipeline
对话式AI短视频创作工具。用户提出想法 → agent 设计脚本 → 人工确认 → 自动制作MP4。 当用户提到：(1) 做个视频/短视频, (2) AI旁白视频, (3) 认知自述/播客风格视频, (4) 文稿转视频。 不要在用户仅提到"视频"、"TTS"、"语音"等模糊词时激活（可能是其他需求）。
As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
ProcedureInfrastructureMedia and videoAI and agentstype 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: 13. 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. 38 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1367 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 151: enough signal without eating the budget
- +4Structure: 16 headings
- +3Step-by-step instructions: 38 items
- +4Has examples (7 code blocks)
- +3All 8 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.
External checks
ClawHub: suspicious
The skill appears to make AI videos as advertised, but users should review it because it sends scripts to external AI services and its default cache can reuse prior media without verifying it matches the current script.
LLM: suspicious (medium) · VirusTotal: · 29 May 2026