Overmind
Overmind is two things in one package:
- Tracing SDK — drop-in observability for LLM agents. Decorate your code, get structured traces of every LLM call and tool invocation.
Documentation: Overmind guide
Console: console.overmindlab.ai
Install
uv tool install overmind
# or
pipx install overmind
Tracing
Wire up tracing once at process start, then annotate the functions you want traced:
import overmind
overmind.init(
service_name="my-agent", providers=["openai", "anthropic"]
) # reads OVERMIND_API_KEY from the environment
@overmind.entry_point()
def run(input_data: dict) -> dict:
return {"response": handle(input_data)}
@overmind.tool()
def search(query: str) -> list[dict]: ...
Available decorators/helpers: entry_point, workflow, tool, function, plus start_span (context manager), set_tag, set_user, and capture_exception for Sentry-style annotations on the current span.
Skills
Use these from Cursor, Codex, or Claude Code to scaffold agents and configure telemetry without leaving your coding environment. Skills live at the repo-root skills/ directory so agent installers can pick them up from this repository (e.g. npx skills add overmind-core/overmind).
overmind skills list --verbose
overmind skills sync "Overmind Telemetry" # or: overmind-agent-telemetry
| Skill | What it does |
|---|---|
Overmind Telemetry |
Add tracing, verify traces via the REST API, and look up current Overmind docs (overmind-agent-telemetry). |
CLI reference
overmind optimise [OPTIONS] Register this machine and run the optimisation loop
overmind skills list [--verbose] List installed/available skills
overmind skills sync <name>... Sync one or more skills to the latest version
Run overmind <command> --help for full flag documentation.
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