Content
72%Weight 40%Scale 1-5Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The skill body is concise and well-structured with clean one-level-deep references to real bundle files, but the STT workflow is stubbed with pseudocode placeholders and neither workflow includes validation checkpoints, capping actionability and workflow clarity at 3. Filling in the transcription snippet and adding verification steps would raise both.
Suggestions
Replace the Workflow 2 stub ('response = speech_client.recognize(...)') with a complete executable snippet, or at minimum inline the recognizer/config setup like tts.md does.
Add a verification step after generation (e.g. confirm the response contains inline_data audio bytes and save to .wav) and after transcription (e.g. check response.results before iterating), since batch/audio output is error-prone.
Make the Quick Start client construction explicit (e.g. note that genai.Client() picks up ADC) so the entry point is copy-paste ready.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The ~35-line body is lean, assumes Claude's competence, and avoids explaining what TTS/STT or the SDKs are; every section earns its place with no padding. | 5 / 5 |
Actionability | Workflow 1 is a complete executable snippet, but Workflow 2 is stubbed with '...' and 'See stt.md', and Quick Start leaves the client argument implicit; concrete guidance is present but incomplete. | 3 / 5 |
Workflow Clarity | Workflows are numbered and sequenced, but there are no validation/verification checkpoints for batch transcription or audio output, and batch/destructive contexts cap clarity at 3 per the guideline. | 3 / 5 |
Progressive Disclosure | The body is a clear overview with five well-signaled one-level-deep references, all of which exist as real files; content is appropriately split with easy navigation. | 5 / 5 |
Total | 16 / 20 Passed |