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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 operate Overmind 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
Skill What it does
Overmind Instrument tracing, inspect telemetry via MCP, upload datasets, run evals, fine-tune, and optimize.

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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