Official Opik skill pack for coding agents. Install it with one command to give your agent
practical guidance for tracing, evaluating, configuring, and debugging LLM applications with
Opik.
This repo contains a number of skills that teach AI coding agents how to work with Opik in real codebases.
After install, your agent can help with tasks like:
- adding Opik tracing to Python or TypeScript apps
- wiring up framework integrations instead of manual instrumentation
- configuring and using `AgentConfig` blueprints
- connecting a local agent to the Opik UI with `opik connect`
- creating and running Test Suites
- tracking multi-turn conversations with `thread_id`
## Install
```bash
npx skills add comet-ml/opik-skills
```
This installs the `opik` skill into your local skills environment.
## What the `opik` skill covers
| Area | Guidance included |
| --- | --- |
| Tracing | Python decorators, TypeScript client tracing, REST API tracing, span types |
| Integrations | OpenAI, Anthropic, LangChain, CrewAI, DSPy, Google ADK, Vercel AI SDK, and more |
| Prompt Library | `client.create_prompt` / `client.get_prompt` (and chat variants), versioning, `metadata` for model/temperature |
| Local Runner | `opik connect`, pairing flow, entrypoint requirements, troubleshooting |
| Evaluation | Test Suites, `run_tests()`, assertions, execution policies, CI gating |
| Conversations | `thread_id`, conversation metrics, common pitfalls |
| Observability | trace boundaries, metadata, feedback scores, distributed tracing |
## One-time Opik setup
These skills are designed to help your coding agent fully integrate Opik into your project, including tracing, evaluations, the Prompt Library, threads, and `opik connect`.
Before using them, authenticate Opik once in the environment where your agent will work:
- Python: run `opik configure`
- TypeScript: run `npx opik-ts configure`
Those commands save your Opik configuration locally, including the API key and connection details the agent will use while wiring up instrumentation.
For setup details, see the [Opik documentation](https://www.comet.com/docs/opik/).
## Example prompts
Once installed, you can ask your agent things like:
- "Add Opik tracing to this FastAPI app."
- "Instrument this TypeScript OpenAI app with Opik."
- "Help me connect this local agent to Opik with `opik connect`."
- "Move these hardcoded model settings into `AgentConfig`."
- "Create a Test Suite for this chatbot."
- "Add `thread_id` support so Opik groups each conversation correctly."
## Repository structure
```text
opik-skills/
├── skills/
│ └── opik/
│ ├── SKILL.md
│ └── references/
│ ├── evaluation.md
│ ├── integrations.md
│ ├── observability.md
│ ├── tracing-python.md
│ ├── tracing-rest-api.md
│ └── tracing-typescript.md
├── README.md
└── LICENSE
```
## Learn more
- [Opik repository](https://github.com/comet-ml/opik)
- [Opik documentation](https://www.comet.com/docs/opik/)
## License
[Apache-2.0](https://github.com/comet-ml/opik-skills/tree/HEAD/LICENSE)
