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incremental-audio-workflow

Step-by-step audio production with per-stem verification, timing alignment, and incremental quality gates

56

Quality

63%

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/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 an excellently sequenced, verification-gated workflow, but it is held back by a duplicated full-script section and a monolithic structure that would benefit from splitting code into bundle files.

Suggestions

Remove the near-duplicate 'Complete Workflow Script' section or move it into a scripts/ file and reference it, eliminating ~200 lines of redundancy.

Extract the large per-step code blocks into a scripts/ bundle (e.g. workflow.py, stems.py) and keep SKILL.md as a concise overview pointing to them, improving progressive disclosure.

Tighten prose sections like 'Key Differences from Standard Workflow' and 'Best Practices' to the non-obvious points only.

DimensionReasoningScore

Conciseness

The per-step code is concrete and not padded with basic-concept explanations, but the 'Complete Workflow Script' section (~200 lines) largely duplicates Steps 1-7, which is unnecessary context that could be trimmed.

2 / 3

Actionability

Every step ships complete, executable Python with imports, real library calls (soundfile, numpy, scipy), and a runnable run_workflow() entry point, making it copy-paste ready.

3 / 3

Workflow Clarity

The seven steps are strictly sequenced with explicit per-step verification, fail-fast raises/sys.exit on failure, and clear feedback loops (verify -> fail -> report), matching the validation-checkpoint anchor.

3 / 3

Progressive Disclosure

Sections are cleanly organized, but the skill is a ~620-line monolithic SKILL.md with all code inline and no bundle files (references/scripts/assets), so content that should be split into separate files is not.

2 / 3

Total

10

/

12

Passed

Description

50%

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 conveys a clear niche and a few specific attributes, but relies on jargon, lists attributes rather than concrete actions, and omits any 'Use when' trigger guidance.

Suggestions

Reword as concrete verbs, e.g. 'Generate, verify, and mix audio stems individually' instead of attribute nouns.

Add an explicit trigger clause, e.g. 'Use when producing multi-stem audio tracks that need per-stem verification and fail-fast error handling.'

Include natural trigger variations users would actually say (e.g. 'mixing stems', 'audio track generation', 'stem workflow').

DimensionReasoningScore

Specificity

Names the audio-production domain and several attributes ('per-stem verification', 'timing alignment', 'incremental quality gates'), but these are noun-phrase attributes rather than a list of concrete verbs, so it is not a comprehensive enumeration of actions.

2 / 3

Completeness

It clearly states what the skill does, but there is no 'Use when...' clause or equivalent explicit trigger guidance, so per the judging guidelines completeness is capped at 2.

2 / 3

Trigger Term Quality

'audio production' is a natural term a user would say, but 'per-stem verification', 'timing alignment', and 'incremental quality gates' are technical jargon with no common variations or colloquial triggers included.

2 / 3

Distinctiveness Conflict Risk

The incremental per-stem approach carves a niche, but 'audio production' could overlap with other audio skills and the absence of distinct triggers leaves some conflict risk.

2 / 3

Total

8

/

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 (648 lines); consider splitting into references/ and linking

Warning

Total

15

/

16

Passed

Repository
HKUDS/OpenSpace
Reviewed

Table of Contents

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