groq-core-workflow-b
Execute Groq secondary workflows: audio transcription (Whisper), vision, text-to-speech, and batch model evaluation. Trigger with phrases like "groq whisper", "groq transcription", "groq audio", "groq vision", "groq TTS", "groq speech".
67
82%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Advisory
Suggest reviewing before use
Quality
Discovery
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 skill description that concisely communicates specific capabilities (audio transcription, vision, TTS, batch evaluation) within the Groq platform context. It includes explicit trigger phrases covering natural user language variations and is clearly distinguishable from other skills. The description uses proper third-person voice and avoids vague language.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: audio transcription (Whisper), vision, text-to-speech, and batch model evaluation. These are distinct, named capabilities. | 3 / 3 |
Completeness | Clearly answers both 'what' (execute Groq secondary workflows: audio transcription, vision, TTS, batch evaluation) and 'when' (explicit trigger phrases provided). The 'Trigger with phrases like...' clause serves as an explicit 'Use when' equivalent. | 3 / 3 |
Trigger Term Quality | Includes natural trigger terms users would say: 'groq whisper', 'groq transcription', 'groq audio', 'groq vision', 'groq TTS', 'groq speech'. These cover common variations of how users would phrase requests. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with the 'Groq' qualifier and specific modality terms (Whisper, TTS, vision). The combination of platform name + specific workflow types makes it very unlikely to conflict with other skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
64%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a solid reference skill with excellent, executable code examples covering multiple Groq secondary workflows. Its main weaknesses are the monolithic structure (all features inline rather than split into focused sub-files) and the lack of validation/error-handling within the workflow steps themselves. The content could be tightened by removing explanatory framing and splitting per-feature examples into referenced files.
Suggestions
Add inline error handling and validation to code examples (e.g., check file exists before streaming, verify transcription result is non-empty) to improve workflow clarity.
Split per-feature code examples (audio, vision, TTS, benchmarking) into separate referenced files to improve progressive disclosure and reduce the monolithic body.
Remove the Overview paragraph's marketing-style framing ('ultra-fast', '216x real-time') and let the model table speak for itself to improve conciseness.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is mostly efficient with good code examples, but includes some unnecessary explanation (e.g., the Overview paragraph explaining Whisper speed stats, 'Beyond chat completions' framing). The model table and error table are useful, but some inline comments in code are redundant for Claude. | 2 / 3 |
Actionability | Fully executable TypeScript and Python code examples covering all described workflows—transcription, translation, vision, TTS, and benchmarking. Code is copy-paste ready with proper imports, types, and realistic parameters. | 3 / 3 |
Workflow Clarity | Steps are clearly labeled and sequenced, but the 'steps' are really independent features rather than a sequential workflow. There are no validation checkpoints—no verification that transcription succeeded, no error handling within the code examples, and no feedback loops for failures like file-too-large scenarios. | 2 / 3 |
Progressive Disclosure | The content is fairly long (~170 lines of substantive content) and could benefit from splitting detailed code examples into separate files. The error table and model reference tables could be externalized. There is one reference to 'groq-common-errors' and external doc links, but the main body is monolithic. | 2 / 3 |
Total | 9 / 12 Passed |
Validation
81%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 9 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
allowed_tools_field | 'allowed-tools' contains unusual tool name(s) | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 9 / 11 Passed | |
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