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Agent skill

Deepgram Text Intelligence

by deepgram in deepgram/deepgram-python-sdk

Uses the Deepgram Python SDK's Read API to analyze text for sentiment, summaries, topics and intents with client.read.v1.text.analyze, from raw text or a hosted URL.

MITAuto-check passedAI & LLM Engineering

Install Deepgram Text Intelligence

skills CLI
$ npx skills add deepgram/deepgram-python-sdk --skill deepgram-python-text-intelligence -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install deepgram/deepgram-python-sdk deepgram-python-text-intelligence --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/deepgram/deepgram-python-sdk.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/deepgram-python-text-intelligence .claude/skills/deepgram-python-text-intelligence && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
deepgram-python-text-intelligence
GitHub stars
469
Token cost
~1.4k tokens
SKILL.md length
412 words
Files
1
Skills in repo
7
Repo updated
First seen
Licence
MIT

At a glance

Uses the Deepgram Python SDK's Read API to analyze text for sentiment, summaries, topics and intents with client.read.v1.text.analyze, from raw text or a hosted URL.

  • Works in 4 steps: In-repo reference: reference.md — "Read… → OpenAPI (REST):… → Context7: library ID… → …
  • Running sentiment analysis on transcripts or chat logs from Python
  • SKILL.md covers When to use this product, Authentication, Quick start and Async equivalent, plus 6 more sections
  • Calls npx

What it does

This skill is for Python code that already has text, such as a transcript, document, chat log or email, and wants quick analytics through a single REST call to /v1/read, with no streaming. It shows loading the API key from the environment, a quick start with client.read.v1.text.analyze and an async version using AsyncDeepgramClient. The request body takes either text or the URL of a hosted plain-text document.

A parameter table covers language, which is required for most analytics and English only for now, plus sentiment, summarize, topics and intents flags, custom topic and intent lists with their modes, and callback, method and tag options. It warns that summarize accepts a boolean only on this endpoint, unlike the v2 option on the audio product. It also sketches the response shape for the summary and sentiment segments. For audio sources it points to the audio intelligence skill. The excerpt is cut off in the API reference.

When your agent uses it

  • Running sentiment analysis on transcripts or chat logs from Python
  • Summarizing a document or email through the Deepgram Read API
  • Detecting topics or intents in text with custom topic lists
  • Reviewing code that calls the Deepgram text analysis endpoint

Example prompts

  • “Analyze the sentiment and topics of this support transcript with the Deepgram Read API.”
  • “Write an async function that summarizes each text file in ./transcripts using Deepgram.”
  • “Add custom intents for refund request and cancellation to our Deepgram text analysis call.”
  • “Review this code that calls client.read.v1.text.analyze and check the summarize parameter.”

Requirements

  • Python with the Deepgram SDK
  • A Deepgram API key

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. In-repo reference: reference.md — "Read V1 Text".
  2. OpenAPI (REST): https://developers.deepgram.com/openapi.yaml
  3. Context7: library ID /llmstxt/developers_deepgram_llms_txt.
  4. Product docs

What it can do on your machine

Read from SKILL.md and the folder at commit 5c2f3af. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • npx

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • developers.deepgram.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Deepgram Text Intelligence loads about 1.4k tokens when it runs. Until then it costs about 128 tokens; SKILL.md has 412 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~128
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from deepgram/deepgram-python-sdk at commit 5c2f3af, republished under its MIT licence (© deepgram). 412 words, ~1,368 tokens.

Download SKILL.mdSave it as .claude/skills/deepgram-python-text-intelligence/SKILL.md (or your agent's skills folder).
name
deepgram-python-text-intelligence
description
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".

Using Deepgram Text Intelligence (Python SDK)

Analyze plain text (or a hosted text URL) for sentiment, summarization, topics, and intents via /v1/read.

When to use this product

  • You have text already (a transcript, document, chat log, email) and want analytics.
  • You want a quick one-shot analysis — REST only, no streaming.

Use a different skill when:

  • The source is audio and you want analytics overlays → deepgram-python-audio-intelligence (same analytics, applied at transcription time).

Authentication

python
from dotenv import load_dotenv
load_dotenv()

from deepgram import DeepgramClient
client = DeepgramClient()

Header: Authorization: Token <api_key>.

Quick start

python
response = client.read.v1.text.analyze(
    request={"text": "Hello, world! This is a sample text for analysis."},
    language="en",
    sentiment=True,
    summarize=True,   # /v1/read is boolean-only (see gotchas)
    topics=True,
    intents=True,
)

if response.results.sentiments:
    print("sentiment avg:", response.results.sentiments.average)
if response.results.summary:
    print("summary:", response.results.summary.text)
if response.results.topics:
    print("topics:", response.results.topics.segments)
if response.results.intents:
    print("intents:", response.results.intents.segments)

Pass request={"text": "..."} for raw text OR request={"url": "https://..."} for a hosted plain-text document.

Async equivalent

python
from deepgram import AsyncDeepgramClient
client = AsyncDeepgramClient()
response = await client.read.v1.text.analyze(request={"text": "..."}, language="en", sentiment=True)

Key parameters

ParamTypeNotes
request{"text": str} or {"url": str}One of these is required
languagestrRequired for most analytics. English only today.
sentimentboolPer-segment + average sentiment
summarizebool/v1/read accepts boolean only. The SDK type alias TextAnalyzeRequestSummarize = typing.Union[typing.Literal["v2"], typing.Any] is shared with Listen and is broader than what Read actually supports — the analyze method docstring states: "For Read API, accepts boolean only." (Listen's summarize="v2" is a different product — see deepgram-python-audio-intelligence.)
topicsboolTopic detection per segment
intentsboolIntent recognition per segment
custom_topic / custom_topic_modelist[str] / strUser-defined topics
custom_intent / custom_intent_modelist[str] / strUser-defined intents
callback, callback_method, tagAsync callback + metadata

Response shape (abridged)

response.results.summary.text
response.results.sentiments.segments[]
response.results.sentiments.average
response.results.topics.segments[]
response.results.intents.segments[]
response.metadata

See reference.md → "Read V1 Text" for full shape. Request body model: ReadV1RequestParams.

API reference (layered)

  1. In-repo reference: reference.md — "Read V1 Text".
  2. OpenAPI (REST): https://developers.deepgram.com/openapi.yaml
  3. Context7: library ID /llmstxt/developers_deepgram_llms_txt.
  4. Product docs:
Show full SKILL.md (175 more words)Show less

Gotchas

  1. Token auth, not Bearer.
  2. English-only for sentiment / summarize / topics / intents today.
  3. summarize on /v1/read is boolean only. Pass True or False. Do not pass "v2" on /v1/read — that's a Listen-only option (see deepgram-python-audio-intelligence). The SDK type Union[Literal["v2"], Any] is shared with Listen and wider than Read actually accepts; the analyze docstring clarifies: "For Read API, accepts boolean only." The generated wire test passing summarize="v2" against a mock server is a Fern artifact and does not indicate real /v1/read support.
  4. language is required for the gated analytics features above.
  5. Body is JSON request=, not query parameters. Don't confuse with /v1/listen which takes audio as the body.
  6. Custom topics/intents need a mode (custom_topic_mode="extended", "strict") or they are ignored.

Example files in this repo

  • examples/40-text-intelligence.py
  • tests/wire/test_read_v1_text.py

Central product skills

For cross-language Deepgram product knowledge — the consolidated API reference, documentation finder, focused runnable recipes, third-party integration examples, and MCP setup — install the central skills:

bash
npx skills add deepgram/skills

This SDK ships language-idiomatic code skills; deepgram/skills ships cross-language product knowledge (see api, docs, recipes, examples, starters, setup-mcp).

© deepgram, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .agents/skills/deepgram-python-text-intelligence of deepgram/deepgram-python-sdk.

Open the folder on GitHubat commit 5c2f3af

Compare with similar skills

Deepgram Text Intelligence next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Deepgram Text Intelligence compared with similar skills
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wdoc Referencethiswillbeyourgithub/wdoc545—~1.1kAutomated safety check: PassAGPL-3.0
Sentence Transformers EmbeddingsOrchestra-Research/AI-Research-SKILLs13k3 repos~1.6kAutomated safety check: PassMIT
Hugging Face Transformers Usagedavila7/claude-code-templates32k12 repos~1.2kAutomated safety check: PassMIT
TransformersK-Dense-AI/scientific-agent-skills48k1 repos~2.8kAutomated safety check: NotesApache-2.0

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Works with

Categories

Questions about Deepgram Text Intelligence

What does Deepgram Text Intelligence do?

Uses the Deepgram Python SDK's Read API to analyze text for sentiment, summaries, topics and intents with client.read.v1.text.analyze, from raw text or a hosted URL. This skill is for Python code that already has text, such as a transcript, document, chat log or email, and wants quick analytics through a single REST call to /v1/read, with no streaming.analyze and an async version using AsyncDeepgramClient.

When should I use Deepgram Text Intelligence?

Deepgram Text Intelligence fits situations like: running sentiment analysis on transcripts or chat logs from Python; summarizing a document or email through the Deepgram Read API; detecting topics or intents in text with custom topic lists; reviewing code that calls the Deepgram text analysis endpoint.

How do I install Deepgram Text Intelligence in Claude Code?

Run `npx skills add deepgram/deepgram-python-sdk --skill deepgram-python-text-intelligence -a claude-code`. Or copy the skill folder (.agents/skills/deepgram-python-text-intelligence in deepgram/deepgram-python-sdk) into .claude/skills/deepgram-python-text-intelligence in your project. Claude Code loads it when a task matches its description.

How do I install Deepgram Text Intelligence in Codex?

Run `npx skills add deepgram/deepgram-python-sdk --skill deepgram-python-text-intelligence -a codex`. Or copy the skill folder (.agents/skills/deepgram-python-text-intelligence in deepgram/deepgram-python-sdk) into .agents/skills/deepgram-python-text-intelligence in your project. Codex loads it when a task matches its description.

Can I use Deepgram Text Intelligence in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add deepgram/deepgram-python-sdk --skill deepgram-python-text-intelligence -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/deepgram-python-text-intelligence, .gemini/skills/deepgram-python-text-intelligence, .github/skills/deepgram-python-text-intelligence and .opencode/skills/deepgram-python-text-intelligence in your project.

What does Deepgram Text Intelligence need to run?

Going by SKILL.md and its folder, Deepgram Text Intelligence needs the command-line tools its instructions call (npx). Our summary lists: Python with the Deepgram SDK; A Deepgram API key.

Does Deepgram Text Intelligence access the network?

SKILL.md names 1 domain. As links in the text: developers.deepgram.com. This is read from the text; nothing was executed.

Is Deepgram Text Intelligence safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Deepgram Text Intelligence use?

Deepgram Text Intelligence is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Deepgram Text Intelligence use?

About 1.4k tokens (SKILL.md is roughly 5.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Deepgram Text Intelligence?

Skills that share tags, products or a category with Deepgram Text Intelligence: Hugging Face Tokenizers (Orchestra-Research/AI-Research-SKILLs, 13k stars), wdoc Reference (thiswillbeyourgithub/wdoc, 545 stars), Sentence Transformers Embeddings (Orchestra-Research/AI-Research-SKILLs, 13k stars) and Hugging Face Transformers Usage (davila7/claude-code-templates, 32k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Deepgram Text Intelligence?

deepgram (a GitHub organization) maintains it in deepgram/deepgram-python-sdk, which has 469 GitHub stars. The repository holds 7 skills in this directory. The repository was last updated on October 6, 2026.

Source: deepgram/deepgram-python-sdk on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.