deepgram/skills

最近记录的来源活动: 2026年10月29日 12:50

SkillsMP 收录数据更新: 2026年11月9日 14:22

已收集 skills: 15

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Follow https://skillsmp.com/skill-install/prompt.md to install Agent Skills from https://github.com/deepgram/skills.

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# Deepgram Skills Skills are folders of instructions and resources that AI coding tools load to help you build with Deepgram faster. Each skill teaches your tool how to use a specific part of the Deepgram platform — from API reference to finding the right starter app. For more information, check out: - [Deepgram Documentation](https://developers.deepgram.com) - [Deepgram API Reference](https://developers.deepgram.com/reference/deepgram-api-overview) - [Ask Deepgram AI](https://developers.deepgram.com/ask-ai) # About This Repository This repository contains skills for building with Deepgram's speech-to-text, text-to-speech, voice agent, and audio intelligence APIs. Skills are agent-agnostic — plain markdown that any AI coding tool can consume. Deepgram ships two actively maintained, industry-leading speech-to-text model families: - **Nova** (`/v1/listen`) — general-purpose transcription with a rich intelligence feature set (diarize, summarize, sentiment, topics, intents). Use for captions, subtitles, batch, and general live streaming. - **Flux STT** (`/v2/listen`, `model=flux-general-en`) — conversational STT with built-in turn detection. Use for voice agents and interactive assistants. See the `api` skill for the full Nova vs Flux STT decision guide. It ships two text-to-speech families on separate endpoints — the voices do not overlap: - **Aura** (`/v1/speak`) — the broadest voice catalog (English, Spanish, German, Dutch, French, Italian, Japanese) plus compressed and containerized output. Use for one-shot synthesis and non-English voices. - **Flux TTS** (`/v2/speak`, `model=flux-{voice}-{language}`) — streaming-first, turn-based synthesis with barge-in and cross-turn voice consistency. Use for voice agents. `model` is required, and only `flux-*` voices are accepted. See the `api` skill for the full Aura vs Flux TTS decision guide. Some skills are hand-written, others are generated from Deepgram's [OpenAPI](https://dpgr.am/openapi.yml) and [AsyncAPI](https://dpgr.am/asyncapi.yml) specs. ## Skills - [./skills](./skills): All Deepgram skills - [./template](./template): Skill template for creating new skills - [./scripts](./scripts): Scripts for fetching specs and generating skills # Skills | Skill | Description | |-------|-------------| | [speech-to-text](./skills/speech-to-text) | Start here for transcription: Nova on `/v1/listen` or Flux STT on `/v2/listen`, a first request, and where to go next | | [text-to-speech](./skills/text-to-speech) | Start here for synthesis: Aura on `/v1/speak` or Flux TTS on `/v2/speak`, a first request, and where to go next | | [voice-agent](./skills/voice-agent) | Start here for a voice agent: the Voice Agent API over one WebSocket, function calling, telephony wiring, and when to use an orchestrator instead | | [audio-intelligence](./skills/audio-intelligence) | Analyze audio, not just transcribe it: `summarize`, `sentiment`, `topics`, `intents`, and `detect_entities` as parameters on `/v1/listen` | | [text-intelligence](./skills/text-intelligence) | Analyze text you already have with the Read API: one `POST /v1/read` with `summarize`, `sentiment`, `topics`, and `intents` | | [browser-agent](./skills/browser-agent) | Run a voice agent in the browser with the Browser Agent SDK: `@deepgram/agents`, `@deepgram/react`, `@deepgram/ui`, and `@deepgram/agents-widget` | | [api](./skills/api) | Full API reference for all Deepgram REST and WebSocket APIs, generated from OpenAPI and AsyncAPI specs | | [docs](./skills/docs) | Find the right Deepgram documentation for any task | | [starters](./skills/starters) | Clone a ready-to-run demo app in your language and start building — 13 frameworks, 8 features | | [recipes](./skills/recipes) | Focused runnable recipes for one feature × one language — minimal working code (< 50 lines) | | [examples](./skills/examples) | Integration examples with third-party platforms (Twilio, LiveKit, LangChain, Vercel AI SDK, etc.) | | [cli](./skills/cli) | Drive Deepgram from the terminal with `deepctl`: install, auth, `dg listen`, `dg speak`, `dg init`, and where to reach for the API instead | | [setup-mcp](./skills/setup-mcp) | Set up the Deepgram MCP server for querying docs directly from your AI coding tool | | [self-hosted](./skills/self-hosted) | Run Deepgram on your own GPUs: licensing, container credentials, and per-target guidance for Docker/Podman, Kubernetes, and Amazon SageMaker | ## SDK-Specific Skills Each Deepgram SDK repository publishes its own set of language-idiomatic skills under `.agents/skills/`: ```bash npx skills add deepgram/deepgram-python-sdk # Python npx skills add deepgram/deepgram-js-sdk # JavaScript / TypeScript npx skills add deepgram/deepgram-java-sdk # Java npx skills add deepgram/deepgram-go-sdk # Go npx skills add deepgram/deepgram-rust-sdk # Rust npx skills add deepgram/deepgram-dotnet-sdk # C# / .NET ``` The Swift and Kotlin SDK repositories are not public, so `npx skills add` cannot reach them; their skills will be listed here once the repositories open. For browser work, use the `browser-agent` skill listed above. It covers the four Browser Agent SDK packages published on npm: `@deepgram/agents`, `@deepgram/react`, `@deepgram/ui`, and `@deepgram/agents-widget`. Each SDK ships 7 product skills named `deepgram-{lang}-{product}`. The full set for the Python SDK: - `deepgram-python-speech-to-text` - `deepgram-python-text-to-speech` - `deepgram-python-text-intelligence` - `deepgram-python-audio-intelligence` - `deepgram-python-voice-agent` - `deepgram-python-conversational-stt` - `deepgram-python-management-api` The `deepgram-{lang}-` prefix keeps names globally unique so installing skills from multiple SDKs never overwrites another SDK's skills. This `deepgram/skills` repo covers product contracts (API reference, docs, starters, recipes, integrations, MCP). The SDK repos cover language-specific usage. # Install ## Any AI coding tool Works with Claude Code, OpenAI Codex, Cursor, Windsurf, GitHub Copilot, Gemini CLI, and [70+ others](https://github.com/vercel-labs/skills). Install the skill for what you are building: ```bash npx skills add deepgram/skills --skill speech-to-text npx skills add deepgram/skills --skill text-to-speech npx skills add deepgram/skills --skill voice-agent ``` Or install every skill in this repository: ```bash npx skills add deepgram/skills ``` The installer detects the agents on your machine. To target agents explicitly, pass `-a` with the agent name (`claude-code`, `codex`, `cursor`), and `--skill` to install one skill: ```bash npx skills add deepgram/skills -a codex -a cursor --skill api ``` ## Claude Code (native plugin system) Register this repository as a plugin marketplace: ``` /plugin marketplace add deepgram/skills ``` Then install the Deepgram plugin: ``` /plugin install deepgram@deepgram-agent-skills ``` This gives you the following slash commands: - `/deepgram:speech-to-text`: Start here for transcription - `/deepgram:text-to-speech`: Start here for synthesis - `/deepgram:voice-agent`: Start here for a voice agent - `/deepgram:audio-intelligence`: Analyze audio on `/v1/listen` - `/deepgram:text-intelligence`: Analyze text with the Read API - `/deepgram:browser-agent`: Run a voice agent in the browser - `/deepgram:api`: Deepgram API reference - `/deepgram:docs`: Find the right documentation - `/deepgram:starters`: Clone a starter app - `/deepgram:recipes`: Focused runnable recipes for one feature × one language - `/deepgram:examples`: Integration examples with third-party platforms - `/deepgram:cli`: Drive Deepgram from the terminal with `deepctl` - `/deepgram:setup-mcp`: Set up the Deepgram MCP server - `/deepgram:self-hosted`: Run Deepgram on your own GPUs You can also install SDK-specific skill plugins from the same marketplace: ``` /plugin install deepgram-js-sdk@deepgram-agent-skills /plugin install deepgram-python-sdk@deepgram-agent-skills /plugin install deepgram-java-sdk@deepgram-agent-skills /plugin install deepgram-go-sdk@deepgram-agent-skills /plugin install deepgram-rust-sdk@deepgram-agent-skills /plugin install deepgram-dotnet-sdk@deepgram-agent-skills ``` Each SDK plugin installs the 7 language-idiomatic skills from that SDK's repository. ## OpenAI Codex Codex loads skills from `.agents/skills/` in your working directory and every directory up to the repository root. Install the Deepgram skills into a project: ```bash npx skills add deepgram/skills -a codex ``` This writes `.agents/skills/<skill>/` for each skill you select. Codex also reads `~/.agents/skills/` for user-wide skills, so add `-g` to install there instead of into the project: ```bash npx skills add deepgram/skills -a codex -g ``` Inside Codex, run `/skills` to browse and apply a skill, or type `$speech-to-text`, `$text-to-speech`, `$voice-agent`, `$audio-intelligence`, `$text-intelligence`, `$browser-agent`, `$api`, `$docs`, `$starters`, `$recipes`, `$examples`, `$cli`, `$setup-mcp`, or `$self-hosted` to invoke one by name. Codex also picks a skill on its own when your task matches its description. Codex reads a project's `AGENTS.md` before working. Use it to tell Codex when to use the Deepgram skills already installed in `.agents/skills/`. To give Codex the live documentation as well, add the Deepgram docs MCP server. `api.dx.deepgram.com/kapa/mcp` rejects an unauthenticated request with HTTP 401 and accepts a Deepgram API key as a bearer token, so pass the key through `--bearer-token-env-var`: ```bash codex mcp add deepgram-docs --url https://api.dx.deepgram.com/kapa/mcp \ --bearer-token-env-var DEEPGRAM_API_KEY ``` `https://developers.deepgram.com/_mcp/server` needs no credential at all. The `setup-mcp` skill covers every path and the tools each one exposes. See [Build skills](https://learn.chatgpt.com/docs/build-skills) and [Custom instructions with AGENTS.md](https://learn.chatgpt.com/docs/agent-configuration/agents-md) in the Codex documentation. ## Cursor The same installer targets Cursor, writing each skill to `.agents/skills/<skill>/` in the project: ```bash npx skills add deepgram/skills -a cursor ``` # Creating a Skill Skills are a folder with a `SKILL.md` file containing YAML frontmatter and instructions. Use the [template](./template/SKILL.md) as a starting point, and read [CONTRIBUTING.md](./CONTRIBUTING.md) for the folder layout, local testing, the review checklist, and the release process: ```markdown --- name: my-skill-name description: A clear description of what this skill does and when to use it. --- # My Skill Name [Instructions that your AI tool will follow when this skill is active] ``` The frontmatter requires two fields: - `name` — A unique identifier for your skill (lowercase, hyphens for spaces) - `description` — What the skill does and when to use it ## Generating API Reference Skills The API reference skills are generated from Deepgram's specs. To regenerate: ```sh # Fetch the latest specs bun run scripts/fetch-specs.ts https://dpgr.am/openapi.yml https://dpgr.am/asyncapi.yml # Generate reference markdown bun install && bun run scripts/generate-skills.ts ```

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