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activePython2026
ContextMesh
See where your agent's tokens go.
An open-source observability layer for AI coding agents. Every step an agent takes — every file read, every test run — is logged to a local, typed, evidence-backed ledger. It publishes one agent-agnostic number that nobody else does: the fraction of tokens spent on tasks that actually finished.
View on GitHubKey metric
useful_context_ratiothe one number that matters
Highlights
- 01Agent-agnostic: traces any agent CLI — Claude Code, Codex, Cursor, Aider, or your own.
- 02Puts provider cache savings and on-top compression side by side, so you can see which actually paid.
- 03Typed, evidence-backed ledger any agent can write to.
- 04119 passing tests, MIT licensed, currently alpha at v0.4.0.
Tags
observabilityai-agentscontext-engineeringtoken-optimizationllm