A collection of 12 agent skills that provide comprehensive knowledge of the Together AI platform — inference, training, embeddings, audio, video, images, function calling, and infrastructure.
Each skill teaches AI coding agents how to use a specific Together AI product, including API patterns, SDK usage (Python and TypeScript), CLI commands, direct API usage, model selection, and best practices. Skills include runnable Python scripts (using the Together Python v2 SDK), TypeScript examples, and CLI/API workflow guidance.
Compatible with Claude Code, Cursor, Codex, and Gemini CLI.
Skills are markdown instruction files that give AI coding agents domain-specific knowledge. When an agent detects that a skill is relevant to your task, it loads the skill's instructions and uses them to write better code.
Each skill contains:
SKILL.md— Lean routing guidance for the agent: when to use the skill, when to hand off, and where to look nextreferences/— Detailed reference docs (model lists, API parameters, CLI commands)scripts/— Runnable Python scripts demonstrating complete workflowsagents/openai.yaml— Optional UI metadata for OpenAI/Codex surfaces
| Skill | Description | Scripts |
|---|---|---|
| together-chat-completions | Real-time and streaming text generation via Together AI's OpenAI-compatible chat/completions API, including multi-tur... | async_parallel.py, chat_basic.py, debug_headers.py, reasoning_models.py, structured_outputs.py, tool_call_loop.py |
| together-images | Text-to-image generation and image editing via Together AI, including FLUX and Kontext models, LoRA-based styling, re... | generate_image.py, kontext_editing.py, lora_generation.py |
| together-video | Text-to-video and image-to-video generation via Together AI, including keyframe control, model and dimension selectio... | generate_video.py, image_to_video.py |
| together-audio | Text-to-speech and speech-to-text via Together AI, including REST, streaming, and realtime WebSocket TTS, plus transc... | stt_realtime.py, stt_transcribe.py, tts_generate.py, tts_websocket.py |
| together-embeddings | Dense vector embeddings, semantic search, RAG pipelines, and reranking via Together AI. | embed_and_rerank.py, rag_pipeline.py, semantic_search.py |
| together-fine-tuning | LoRA, full fine-tuning, DPO preference tuning, VLM training, function-calling tuning, reasoning tuning, and BYOM uplo... | dpo_workflow.py, finetune_workflow.py, function_calling_finetune.py, reasoning_finetune.py, vlm_finetune.py |
| together-batch-inference | High-volume, asynchronous offline inference at up to 50% lower cost via Together AI's Batch API. | batch_workflow.py |
| together-evaluations | LLM-as-a-judge evaluation framework on Together AI. | run_evaluation.py |
| together-sandboxes | Remote Python execution in managed sandboxes on Together AI with stateful sessions, file uploads, data analysis, char... | execute_with_session.py |
| together-dedicated-endpoints | Single-tenant GPU endpoints on Together AI with autoscaling and no rate limits. | deploy_finetuned.py, manage_endpoint.py, upload_custom_model.py |
| together-dedicated-containers | Custom Dockerized inference workers on Together AI's managed GPU infrastructure. | queue_client.py, sprocket_hello_world.py |
| together-gpu-clusters | On-demand and reserved GPU clusters (H100, H200, B200) on Together AI with Kubernetes or Slurm orchestration, shared ... | manage_cluster.py, manage_storage.py |
Install all skills at once using skills.sh:
npx skills add togethercomputer/skillsThis works with Claude Code, Cursor, Codex, and other agents that support the Agent Skills specification.
cp -r skills/together-* your-project/.claude/skills/
# Global availability
cp -r skills/together-* ~/.claude/skills/Marketplace plugin coming soon.
cp -r skills/together-* your-project/.cursor/skills/Cursor plugin marketplace listing coming soon.
cp -r skills/together-* your-project/.agents/skills/gemini extensions install https://github.com/togethercomputer/skills.git --consent# Claude Code
ls your-project/.claude/skills/together-*/SKILL.md
# Codex
ls your-project/.agents/skills/together-*/SKILL.mdYou should see one SKILL.md per installed skill.
Once installed, skills activate automatically when the agent detects a relevant task. No explicit invocation is needed.
Chat completions — Ask the agent to build a chat app:
> Build a multi-turn chatbot using Together AI with Llama 3.3 70B
The agent will use the together-chat-completions skill to generate correct v2 SDK code with proper model IDs, parameters, and streaming patterns.
Function calling — Ask for tool-using agents:
> Create an agent that can check weather and stock prices using Together AI function calling
The agent will reference together-chat-completions for the complete tool call loop pattern, including parallel tool calls and tool_choice options.
Image generation — Ask for image workflows:
> Generate a FLUX image with Together AI and save it locally as PNG
The agent will use together-images to write code with the correct model ID, base64 decoding, and file saving.
Fine-tuning — Ask to fine-tune a model:
> Fine-tune Llama 3.1 8B on my dataset using Together AI with LoRA
The agent will reference together-fine-tuning for data format requirements, training parameters, monitoring, and deployment.
Each script is a standalone, runnable example. They require the Together Python SDK and an API key:
uv pip install "together>=2.0.0"
export TOGETHER_API_KEY=your_key
# Run any script directly
python skills/together-images/scripts/generate_image.py
python skills/together-audio/scripts/tts_generate.py
python skills/together-batch-inference/scripts/batch_workflow.pyScripts use the Together Python v2 SDK (together>=2.0.0) with keyword-only arguments, updated method names, and current response shapes.
togetherai-skills/
├── quality/
│ └── trigger-evals/ # Skill trigger test sets
├── scripts/ # Repo tooling, generators, validators
└── skills/
└── together-<product>/
├── SKILL.md # Core instructions (always loaded on trigger)
├── agents/
│ └── openai.yaml # OpenAI/Codex interface metadata
├── references/ # Detailed docs (loaded when needed)
│ ├── models.md # Supported models, IDs, context lengths
│ ├── api-reference.md
│ └── ...
└── scripts/ # Runnable Python examples (v2 SDK)
└── <workflow>.py
- Metadata (YAML frontmatter) — Always available to the agent (~100 words). Used to decide whether to load the skill.
- Body (Markdown) — Loaded when the skill is triggered. It should stay lean and focus on routing, high-signal rules, and the next resource to open.
- References — Loaded on demand when the agent needs deeper detail (model lists, full API specs).
- Scripts — Available as runnable code that the agent can reference or execute directly.
- OpenAI metadata —
agents/openai.yamlgives OpenAI/Codex surfaces a display name, short description, and default prompt.
This repo now treats skills as agent artifacts rather than long tutorials:
SKILL.mdfiles are intentionally short and routing-oriented- Long references include a
## Contentssection near the top - Each skill has trigger eval examples in
quality/trigger-evals/ - Multi-step Python workflows are validated for current v2 SDK usage and safer tempfile handling
Version bump: This repo now requires
together>=2.0.0. If you are upgrading from v1, see the migration guide for breaking changes in method names, argument styles, and response shapes.
All code examples and scripts target the Together Python v2 SDK (together>=2.0.0), which uses:
- Keyword-only arguments (not positional)
client.batches.create()/client.batches.retrieve()(notcreate_batch()/get_batch())client.endpoints.retrieve()(notget())client.code_interpreter.execute()(notrun())client.evals.create()(notclient.evaluation.create())- File objects via context managers (
with open(..., "rb") as f:) - Typed parameter classes for evaluations
If you're using the v1 SDK, see the migration guide.
- A supported AI coding agent: Claude Code, Cursor, Codex, or Gemini CLI
- Together AI API key
- Python 3.10+ (for scripts)
uv pip install "together>=2.0.0"(v2 SDK)
MIT