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acestep

AI music generation with ACE-Step 1.5 — background music, vocal tracks, covers, stem extraction for video production. Use when generating music, soundtracks, jingles, or working with audio stems. Triggers include background music, soundtrack, jingle, music generation, stem extraction, cover, style transfer, or musical composition tasks.

67

Quality

84%

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SKILL.md
Quality
Evals
Security

Quality

Content

65%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is exceptionally actionable — complete executable commands, presets, and concrete prompt examples for every task type — but it is held back by duplicated guidance, two redundant full lyric examples, missing validation/error-recovery steps in its workflows, and a fully inlined structure with no reference files. Tightening the duplication and adding an output-verification step would lift it substantially.

Suggestions

Consolidate the duplicated lyric guidance (UPPERCASE intensity, parenthetical backing vocals, 6-10 syllables per line) into the "Lyrics Formatting" section only, and keep a single full lyric example instead of both the four-verse song and the Tech Product Jingle.

Add a validation checkpoint to the generation workflow: after generating, verify the output file exists and its duration matches --duration (within the stated 0.1s precision), and note the retry path (e.g., reuse --seed to iterate on prompt/lyrics, or re-run --setup if the endpoint errors).

Move the prompt-engineering deep dive and lyric syntax reference into a references/ file (e.g., PROMPTING.md), keeping SKILL.md as a concise overview with quick-reference commands and preset tables linked to it.

DimensionReasoningScore

Conciseness

The "UPPERCASE = high intensity", "Parentheses = background vocals", and "6-10 syllables per line" guidance appears in both "Key tips for good results" and "Lyrics Formatting", and two full lyric examples (the four-verse song and the Tech Product Jingle) are given where one would teach the same syntax. Not 4 because the duplication and double lyric blocks go beyond minor trimming; not 2 because there is no padding that explains concepts Claude already knows.

3 / 5

Actionability

Every task type has copy-paste-ready commands with concrete flags (--bpm 128, --key "G Major", --cover-strength values with semantic meanings, stem track names), plus tables of presets and scene-to-preset mappings, a good/bad caption pair, and an executable Remotion mixing snippet. Common cases are covered end to end.

5 / 5

Workflow Clarity

Sequences are present (numbered "Creating a Song" progression and the four-step "Timing Workflow"), but there are no validation checkpoints or error-recovery guidance — no step verifies the output file exists or that its duration matches --duration, and nothing covers what to do if the RunPod endpoint fails. This matches anchor 3 (sequence present, checkpoints missing) rather than 4, which requires most checkpoints.

3 / 5

Progressive Disclosure

The single ~265-line file is well-sectioned with clear headers, but no bundle files exist — the prompt-engineering deep dive, lyric formatting reference, and video-production integration tables are all inlined where reference files would keep SKILL.md an overview. This fits anchor 3 (some structure, content that should be separate is inline) better than 4, which expects most heavy content split out.

3 / 5

Total

14

/

20

Passed

Description

96%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description that explicitly states concrete capabilities and explicit trigger conditions with natural keyword coverage. The only weakness is that "cover" and "style transfer" are generic enough to risk overlap with visual/audio-adjacent skills, and the third sentence's trigger enumeration is largely redundant with the "Use when" clause.

DimensionReasoningScore

Specificity

"AI music generation with ACE-Step 1.5 — background music, vocal tracks, covers, stem extraction for video production" names the tool and four concrete capabilities that comprehensively cover its task types. Not 4 because the action list matches the skill's full feature set rather than having minor gaps.

5 / 5

Completeness

Explicitly answers what ("background music, vocal tracks, covers, stem extraction") and when ("Use when generating music, soundtracks, jingles, or working with audio stems") with concrete trigger phrases. This matches the anchor-5 pattern of capability list followed by an explicit Use-when clause, so no lower anchor fits.

5 / 5

Trigger Term Quality

"background music, soundtrack, jingle, music generation, stem extraction, cover, style transfer, or musical composition tasks" covers the natural synonyms a user would actually say, with both capability words and task-request phrasings. Not 4 because coverage extends beyond the common core terms to variations like "style transfer" and "musical composition".

5 / 5

Distinctiveness Conflict Risk

Music generation and stem extraction are a clear niche, but the bare terms "cover" and "style transfer" could also match image-cover or visual style-transfer skills, creating minor overlap risk. Not 5 because of that ambiguity; not 3 since the domain framing ("AI music generation", "audio stems") keeps it mostly distinct.

4 / 5

Total

19

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

calesthio/OpenMontage

Path

.agents/skills/acestep/SKILL.md

Reviewed

Table of Contents

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