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whisper

Transcribe audio files to text using OpenAI Whisper

60

Quality

71%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

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tessl review fix ./examples/skill/skills/whisper/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

88%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 a lean, executable reference for a single-purpose CLI skill: complete commands, a concrete parameter spec, and useful comparison tables, with no concept explanations padding it out. Its only real weaknesses are minor redundancy in the Capabilities section and description-level issues carried from the frontmatter.

DimensionReasoningScore

Conciseness

The body is efficient — tables for model sizes and a compact parameter list instead of prose — but the '## Capabilities' bullet list and the opening sentence largely duplicate the Usage/Parameters sections and could be trimmed.

4 / 5

Actionability

All commands are copy-paste ready with concrete example arguments ('--model medium', '--language zh', '--timestamps', '--format json'), the referenced script exists at scripts/transcribe.py, and the common cases (model choice, language, timestamps, JSON output) are each specifically covered.

5 / 5

Workflow Clarity

This is a simple single-action skill and that action is unambiguous — one command with fully documented arguments — so the simple-skill exception applies; there are no destructive or batch operations that would require validation checkpoints.

5 / 5

Progressive Disclosure

Content is well organized into clear sections with a correctly-referenced bundle script (scripts/transcribe.py, verified to exist) at one level of depth; the model-size and format tables could arguably live in a reference file, which keeps this just short of the top anchor.

4 / 5

Total

18

/

20

Passed

Description

53%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.

The description is concise and states a clear single capability, but it reads as a bare 'what' statement. It lacks any 'when to use' trigger guidance and common synonyms (transcription, speech-to-text, MP3/WAV), limiting both completeness and trigger-term quality.

Suggestions

Add a 'Use when...' clause, e.g. 'Use when the user asks to transcribe audio, generate subtitles, or convert speech to text, or mentions audio files (MP3, WAV, M4A) or Whisper.'

Include natural synonyms and file extensions — 'transcription', 'speech-to-text', 'captions/subtitles', 'MP3', 'WAV' — so the skill triggers on the phrasings users actually say.

Optionally surface 1-2 more concrete capabilities (timestamp generation, 90+ language auto-detection) to raise specificity from one action to several.

DimensionReasoningScore

Specificity

The description names the domain ('audio files') and one concrete action ('Transcribe... to text') but stops there, matching the anchor for 1-2 concrete actions without comprehensive coverage — it omits timestamps, languages, model sizes, and output formats that the skill actually supports.

3 / 5

Completeness

It has a clear 'what' (transcribe audio files to text using OpenAI Whisper) but no 'when' guidance at all; per the judging guidelines, a missing 'Use when...' clause caps completeness at 3.

3 / 5

Trigger Term Quality

It includes relevant keywords like 'Transcribe', 'audio files', and 'OpenAI Whisper', but misses common variations users would say — 'transcription', 'speech-to-text', 'subtitles', and file extensions like MP3 or WAV.

3 / 5

Distinctiveness Conflict Risk

The audio-transcription niche with named tooling (OpenAI Whisper) is mostly distinct with clear triggers, with only minor overlap risk against general audio/media manipulation skills.

4 / 5

Total

13

/

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
trpc-group/trpc-agent-go
Reviewed

Table of Contents

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