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deepgram-python-text-intelligence

Use when writing or reviewing Python code in this repo that calls Deepgram Text Intelligence / Read (`/v1/read`) for sentiment, summarization, topic detection, and intent recognition on text input. Covers `client.read.v1.text.analyze(...)` with body `text` or `url`. Use `deepgram-python-audio-intelligence` when the source is audio instead of text. Triggers include "read API", "text intelligence", "analyze text", "sentiment", "summarize text", "topics", "intents", "read.v1".

76

Quality

94%

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SecuritybySnyk

Low

Low-risk findings worth noting

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.

A strong, highly actionable reference skill: executable code for sync and async, a concrete parameter table, and genuinely non-obvious gotchas (Token auth, boolean-only summarize, required language). The main weaknesses are the triple-stated summarize caveat, which inflates token cost for one point, and reliance on an unbundled reference.md for the full response shape.

Suggestions

State the summarize boolean-only constraint once (in Gotchas) and reduce the params-table cell to a short note — the full type-alias quote and Fern-artifact explanation are currently duplicated across two sections.

Move the SDK type-alias detail (Union[Literal["v2"], Any]) and the wire-test caveat into reference.md, keeping only 'boolean only on /v1/read; "v2" is Listen-only' inline.

If the skill is distributed outside the repo, bundle reference.md (or an abridged Read V1 Text section) so the 'See reference.md for full shape' pointer resolves within the skill.

DimensionReasoningScore

Conciseness

The body is dense and information-rich (tables, executable snippets, six real gotchas) with no explanations of concepts Claude already knows, but the summarize-boolean-only point is repeated three times — a quick-start comment, a params-table cell quoting the full type alias, and gotcha #3 re-quoting it plus the Fern note. That trimmable over-explanation matches the 'minor instances that could be trimmed' anchor rather than the every-token-earns-its-place level of 5.

4 / 5

Actionability

The quick start and async snippets are copy-paste executable end-to-end, the params table gives concrete types and values (e.g., custom_topic_mode="extended"/"strict"), and the response-shape block shows exact attribute paths. Fully executable guidance covering the common cases; not 4 because there are no missing key details for the primary use case.

5 / 5

Workflow Clarity

This is a simple, single-purpose skill (authenticate, call analyze, read results) and that single action is unambiguous, with auth, quick start, params, and response shape each in clearly ordered sections. No destructive or batch operations exist, so the validation cap does not apply; the simple-skill exception for a 5 is met.

5 / 5

Progressive Disclosure

Structure is good: a layered, one-level-deep reference list (in-repo reference.md, OpenAPI, Context7, product docs), an abridged response shape with a pointer to the full shape, and clear section headers. It falls short of 5 because the primary deep-dive reference (`reference.md`) is not present in the skill bundle — no references/ directory exists — so the main offload target is unverifiable, and the body exceeds the under-50-line simple-skill case.

4 / 5

Total

18

/

20

Passed

Description

100%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.

An exemplary description: concrete capabilities, the exact SDK call signature, an explicit use-when clause with natural trigger phrases, and explicit disambiguation against the sibling audio-intelligence skill. Nothing vague or padded; every clause either states a capability or a trigger.

DimensionReasoningScore

Specificity

The description lists multiple concrete capabilities ("sentiment, summarization, topic detection, and intent recognition") and names the exact SDK call "client.read.v1.text.analyze(...)" with both accepted body forms ("text" or "url"). This matches the comprehensive-coverage anchor; it is not 4 because there are no meaningful gaps in the capability enumeration.

5 / 5

Completeness

Both questions are answered explicitly: the what (analytics on text via /v1/read with the specific SDK method and body options) and the when ("Use when writing or reviewing Python code in this repo that calls Deepgram Text Intelligence / Read"), plus concrete trigger phrases. This matches the top anchor; a 4 would require the 'when' to be less explicit than it is.

5 / 5

Trigger Term Quality

It provides an explicit, comprehensive trigger list — "read API", "text intelligence", "analyze text", "sentiment", "summarize text", "topics", "intents", "read.v1" — covering natural user phrasings, synonyms, and the API path. This is the comprehensive-synonyms anchor, above the good-but-few-missing level of 4.

5 / 5

Distinctiveness Conflict Risk

It carves out a clear niche (text-only /v1/read analytics) and actively disambiguates the closest sibling: "Use `deepgram-python-audio-intelligence` when the source is audio instead of text." Conflict risk with other skills is minimal; not 4 because the overlap concern is not just minor but explicitly resolved.

5 / 5

Total

20

/

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
deepgram/deepgram-python-sdk
Reviewed

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