AD wechat-article-video
Convert Chinese WeChat public-account articles and supplied images into publish-ready vertical WeChat Channels videos. Use for 公众号转视频、图文转视频、医药或药械招商、企业和产品推荐、视频号日更、批量出片, including article analysis, fact-safe scripting, 9:16 layout direction, edge-tts narration, subtitle synchronization, HyperFrames or Remotion rendering, visible first-frame covers, and delivery QA.
Convert Chinese WeChat public-account articles and supplied images into publish-ready vertical WeChat Channels videos.
As a process D 45/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, failures and branches
The same skill appears in 1 more place: ClawHub
How to improve
- 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: 14. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 45/100
- 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
- 30Running it twice. 5 mutating operations with no state check
- 40Consistency. Frontmatter name (wechat-article-video) differs from the folder (wechat-article-video-skill)
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 100Steps. 63 steps
- 100Execution cost. Instruction body is 2591 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
- +2Single-language instructions
- +3Description length 365: enough signal without eating the budget
- +4Structure: 14 headings
- +3Step-by-step instructions: 63 items
- +4Has examples (6 code blocks)
- +4Reference files are cited in the instructions (4 of 4)
- +3All 5 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.