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adaptive-stem-alignment

Incremental audio production with duration mismatch handling, adaptive stem extension, and pre-mix alignment verification

58

Quality

67%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./benchmarks/gdpval/skills/audio-track-production-enhanced-enhanced-b8f537/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

77%

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

The body is highly actionable with executable code and excellent workflow sequencing with verification checkpoints, but it is a long monolithic file with some redundant strategy guidance that hurts conciseness and progressive disclosure.

Suggestions

Move the large alignment routine and/or strategy-selection detail into a reference file (e.g. ALIGNMENT.md) and link to it, leaving the core workflow inline.

Remove the duplicate strategy-selection guide in Troubleshooting since the same table already appears in Step 5.

Tighten or factor out the long `align_stem_duration` crossfade branch to reduce token weight.

DimensionReasoningScore

Conciseness

The ~700-line body is mostly lean executable code rather than concept explanation, but the duration-mismatch strategy table in Step 5 is duplicated by the "Strategy Selection Guide" in Troubleshooting, and the full alignment routine is long enough that it could be tightened or factored out.

2 / 3

Actionability

Every step ships complete, executable Python with concrete functions, real library calls (soundfile, numpy, scipy), and copy-paste-ready driver loops rather than pseudocode.

3 / 3

Workflow Clarity

Eight steps are given in strict order, each with immediate verification and fail-fast `raise RuntimeError` feedback loops, plus a final verification checklist — matching the explicit-validation anchor.

3 / 3

Progressive Disclosure

The skill is a single monolithic ~700-line SKILL.md with no bundle files or external references; it is well-sectioned but content that could be split (strategy guide, full alignment code) is all inline.

2 / 3

Total

10

/

12

Passed

Description

57%

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

The description is specific to a clear audio-production niche but relies on technical feature nouns rather than concrete actions and omits an explicit "Use when" trigger, capping completeness and trigger-term quality at 2.

Suggestions

Add an explicit trigger clause, e.g. "Use when generating multi-stem audio tracks where stems may have differing durations or when aligning stems before mixing."

Reframe feature nouns as concrete verbs/actions (e.g. "generate, align, verify, and mix stems") to raise specificity.

Include natural user phrasings like "stems", "mixing", and "align audio" alongside the technical terms.

DimensionReasoningScore

Specificity

"Incremental audio production with duration mismatch handling, adaptive stem extension, and pre-mix alignment verification" names the domain (audio production) and several specific concerns, but lists feature noun-phrases rather than concrete executable actions, so it stops short of the comprehensive multiple-actions anchor.

2 / 3

Completeness

The description states what the skill does but contains no "Use when..." or equivalent trigger guidance, which per the rubric caps completeness at 2.

2 / 3

Trigger Term Quality

Terms like "audio production", "stem extension", and "duration mismatch" are relevant but lean technical; common natural phrasings (e.g. "mixing", "stems", "align stems") appear only partially and there is no explicit trigger clause.

2 / 3

Distinctiveness Conflict Risk

The narrow focus on stem duration alignment and pre-mix verification forms a clear niche with distinct triggers unlikely to fire for unrelated skills.

3 / 3

Total

9

/

12

Passed

Validation

93%

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

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (739 lines); consider splitting into references/ and linking

Warning

Total

15

/

16

Passed

Repository
HKUDS/OpenSpace
Reviewed

Table of Contents

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