AC senseaudio-songmaker
Generate a complete song from a text description — AI writes lyrics then composes music. Use when users want to create a song, turn a description into audio, or generate background music. Triggers on "帮我写一首关于夏天的流行歌曲", "用这段歌词生成一首摇滚歌曲", "生成一首纯音乐背景曲", "AI 作词作曲", "作曲", "写歌", "给我生成一首歌".
As a process C 58/100 · Has gaps — weak spots: steps, inputs and preconditions, consistency
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: 2. 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 58/100
- 0Steps. Prose only: no discrete steps
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 40Consistency. Frontmatter name (senseaudio-songmaker) differs from the folder (songmaker)
- 60Result and completion. Output format stated, no completion criterion
- 70When it triggers. States when to use, but not when not to
- 100Tools and files. No external tools needed
- 100Failures and branches. 4 branches, has a failure section
- 100Execution cost. Instruction body is 789 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)
- +3No numbered steps or checklist
- +1No license
- +2Single-language instructions
- +5Description quotes 5 example trigger phrases
- +3Description length 282: enough signal without eating the budget
- +4Structure: 6 headings
- +3Output format is stated explicitly
- +4Has examples (9 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.