whisper

Transcribe audio files to text using OpenAI Whisper

Quality

71%

Does it follow best practices?

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Securityby

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./examples/skill/skills/whisper/SKILL.md

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 well-structured and highly actionable with executable commands and a real bundled script, staying lean without explaining concepts Claude already knows.

Dimension	Reasoning	Score
Conciseness	Lean and free of concept explanations, with only minor redundancy between the "Capabilities" list and the "Parameters" section that could be trimmed.	4 / 5
Actionability	Provides fully executable, copy-paste-ready commands covering the common cases (model size, language, timestamps, JSON output) and the referenced scripts/transcribe.py exists.	5 / 5
Workflow Clarity	A simple single-purpose skill whose single action (run the transcribe script) is unambiguous, meeting the simple-skill exception; transcription is not a destructive/batch operation requiring validation checkpoints.	5 / 5
Progressive Disclosure	Well-organized sections with a clear one-level reference to scripts/transcribe.py (which exists), but at ~72 lines it exceeds the under-50-line simple-skill threshold so it does not fully qualify for a 5 on structure alone.	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 clearly states what the skill does and names the specific tool, but omits any "Use when..." trigger guidance and lacks synonyms or file-extension terms that users would naturally say.

Suggestions

Add a "Use when..." clause naming natural triggers, e.g. "Use when transcribing audio, converting speech to text, or generating subtitles from audio files."

Include common synonyms and file extensions (speech to text, dictation, .mp3, .wav, .m4a) to improve trigger-term coverage.

Mention a second concrete capability (e.g. timestamp or JSON output) to raise specificity beyond a single action.

Dimension	Reasoning	Score
Specificity	Names the domain (audio transcription) and one concrete action ("Transcribe audio files to text") but offers no broader coverage of capabilities, matching the 1-2 concrete actions anchor.	3 / 5
Completeness	Has a clear "what" but no "Use when..." clause or equivalent trigger guidance, so per the missing-trigger cap completeness stays at 3.	3 / 5
Trigger Term Quality	Includes relevant keywords ("transcribe", "audio files", "text", "OpenAI Whisper") but misses common variations like "speech to text", "dictation", "subtitles", or file extensions such as .mp3/.wav.	3 / 5
Distinctiveness Conflict Risk	The named tool (OpenAI Whisper) and audio-transcription niche make it mostly distinct with only minor overlap risk against general media/speech skills; not a 5 because no explicit trigger phrase is present.	4 / 5
	Total	13 / 20 Passed

Validation

100%

Warnings & errors only

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
Path: examples/skill/skills/whisper/SKILL.md
Commit: 9f7e561

Reviewed: ~16 hours ago

Table of Contents

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