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voice-refine

Transform verbose voice input into structured, token-efficient Claude prompts. Use when cleaning up voice memos, dictation output, or speech-to-text transcriptions that contain filler words, repetitions, and unstructured thoughts.

63

Quality

75%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./examples/skills/voice-refine/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

50%

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

This skill provides a reasonable framework for voice-to-prompt transformation with a clear pipeline and output template, but falls short on actionability — the most critical gap is the missing 'after' example showing what the refined output looks like for the given French voice input. The flags table implies CLI tooling that isn't implemented or referenced, and the filtering rules largely describe what Claude would naturally do without instruction.

Suggestions

Add a complete before-and-after example showing the French voice input transformed into the structured output format — this is the single most impactful improvement for actionability.

Remove or significantly trim the Filtering Rules section, as Claude already knows how to identify filler words and preserve technical requirements.

Integrate the --confirm validation step explicitly into the transformation pipeline (e.g., step 5: present to user for confirmation before sending).

Either provide the referenced bundle files (examples/before-after.md) or remove the 'See Also' references to non-existent files.

DimensionReasoningScore

Conciseness

Mostly efficient but includes some unnecessary sections like the Compression Metrics table and the Filtering Rules section which largely describe things Claude already knows how to do. The flags table describes CLI features that aren't clearly tied to an implementation.

2 / 3

Actionability

The transformation pipeline and output format template are helpful, but there's no executable code or concrete implementation. The pipeline steps (DEDUPE, EXTRACT, STRUCTURE, COMPRESS) are described at a high level without showing how to actually perform them. The before/after example shows input but not the actual refined output.

2 / 3

Workflow Clarity

The 4-step pipeline is clearly sequenced, and the output format provides a good template. However, there's no validation checkpoint — no step to verify information retention or confirm with the user that intent was preserved before proceeding. The --confirm flag implies a validation step but it's not integrated into the workflow.

2 / 3

Progressive Disclosure

References to 'guide/ai-ecosystem.md' and 'examples/before-after.md' are well-signaled, but no bundle files exist to support them. The content is reasonably organized with clear sections, but the filtering rules and compression metrics could potentially be in a separate reference file to keep the main skill leaner.

2 / 3

Total

8

/

12

Passed

Description

100%

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

This is a strong, well-crafted description that clearly communicates a specific capability (transforming voice input into structured prompts), includes an explicit 'Use when' clause with natural trigger terms, and occupies a distinct niche. It uses proper third-person voice and is concise without being vague. The description covers multiple natural keyword variations that users would actually say when needing this skill.

DimensionReasoningScore

Specificity

Lists specific concrete actions: 'Transform verbose voice input into structured, token-efficient Claude prompts' and describes the types of content it handles (filler words, repetitions, unstructured thoughts). Multiple specific capabilities are named.

3 / 3

Completeness

Clearly answers both 'what' (transform verbose voice input into structured, token-efficient prompts) and 'when' (explicit 'Use when' clause covering voice memos, dictation output, speech-to-text transcriptions with filler words, repetitions, and unstructured thoughts).

3 / 3

Trigger Term Quality

Includes strong natural trigger terms users would say: 'voice input', 'voice memos', 'dictation output', 'speech-to-text', 'transcriptions', 'filler words', 'repetitions'. Good coverage of variations a user might naturally use.

3 / 3

Distinctiveness Conflict Risk

Occupies a clear niche at the intersection of voice/speech-to-text processing and prompt optimization. The combination of voice input cleanup + prompt structuring is highly distinctive and unlikely to conflict with general text editing or prompt engineering skills.

3 / 3

Total

12

/

12

Passed

Validation

90%

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

Validation10 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

10

/

11

Passed

Repository
FlorianBruniaux/claude-code-ultimate-guide
Reviewed

Table of Contents

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