deepgram-sdk-patterns
Apply production-ready Deepgram SDK patterns for TypeScript and Python. Use when implementing Deepgram integrations, refactoring SDK usage, or establishing team coding standards for Deepgram. Trigger: "deepgram SDK patterns", "deepgram best practices", "deepgram code patterns", "idiomatic deepgram", "deepgram typescript".
80
77%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./plugins/saas-packs/deepgram-pack/skills/deepgram-sdk-patterns/SKILL.mdQuality
Discovery
89%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 well-structured skill description with clear 'what' and 'when' clauses and explicit trigger terms. Its main weakness is that the specific capabilities are somewhat high-level — it says 'production-ready patterns' without detailing what those patterns cover (e.g., streaming, batch transcription, WebSocket handling). The distinctiveness is excellent due to the narrow Deepgram focus.
Suggestions
Add more concrete actions to improve specificity, e.g., 'Configure streaming transcription, handle WebSocket connections, set up authentication, manage API callbacks' rather than the general 'apply production-ready patterns'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | It names the domain (Deepgram SDK) and mentions some actions ('implementing integrations', 'refactoring SDK usage', 'establishing team coding standards'), but these are fairly high-level and don't list concrete specific actions like 'configure streaming transcription', 'handle WebSocket connections', or 'set up authentication'. | 2 / 3 |
Completeness | Clearly answers both 'what' (apply production-ready Deepgram SDK patterns for TypeScript and Python) and 'when' (implementing integrations, refactoring SDK usage, establishing coding standards) with explicit trigger terms listed. | 3 / 3 |
Trigger Term Quality | Includes explicit trigger terms that users would naturally say: 'deepgram SDK patterns', 'deepgram best practices', 'deepgram code patterns', 'idiomatic deepgram', 'deepgram typescript'. Also mentions TypeScript and Python as languages. Good coverage of natural search terms. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive — Deepgram is a specific third-party SDK, and the description is narrowly scoped to Deepgram SDK patterns for TypeScript and Python. Very unlikely to conflict with other skills. | 3 / 3 |
Total | 11 / 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 highly actionable skill with production-ready, executable code examples covering multiple Deepgram SDK use cases across TypeScript and Python. Its main weaknesses are length (too much inline for a single SKILL.md with no bundle support files) and lack of validation checkpoints between steps. The content would benefit from splitting into focused sub-files and adding verification steps.
Suggestions
Split Python patterns, v5 migration notes, and typed response helpers into separate referenced files (e.g., PYTHON_PATTERNS.md, MIGRATION_V5.md) to improve progressive disclosure and reduce the main file's token footprint.
Add validation checkpoints such as 'verify API key with a test transcription before proceeding' and 'confirm TTS output file is non-empty and playable' to strengthen workflow clarity.
Remove the 'Output' section which merely restates what was already demonstrated, and trim the Aura voice options comment to a reference link instead.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is mostly efficient with executable code examples, but includes some unnecessary elements like the voice options comment block, the Output section that just restates what was already shown, and the typed response helpers which Claude could generate on its own. The content could be tightened by ~30%. | 2 / 3 |
Actionability | All code examples are fully executable, copy-paste ready TypeScript and Python with correct imports, concrete API calls, specific model names, and real SDK method signatures. The error handling table provides specific error-to-solution mappings. | 3 / 3 |
Workflow Clarity | Steps are clearly numbered and sequenced, but they function more as independent patterns than a connected workflow. There are no validation checkpoints between steps—for example, no guidance on verifying the API key works before proceeding, or validating audio output after TTS generation. | 2 / 3 |
Progressive Disclosure | The content is a long monolithic file (~200 lines of code) with no bundle files to offload detail into. The Python patterns, typed helpers, and v5 migration notes could each be separate referenced files. External links to docs are provided but internal structure is flat. | 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 | |
- Commit
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- Reviewed
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