Fitness tracker dashboard for AI coding agents (Claude Code, Codex). Visualize usage, cost, tokens, and productivity from local conversation logs.

MCP server for agentfit: token-aware message truncation. Fit a chat history into the model's context budget with drop-oldest, drop-middle, or priority strategies.

Local-first tests for AGENTS.md and coding-agent instructions.

Fit your messages into the LLM context window. Token-aware truncation with multiple strategies (drop-oldest, drop-middle, priority), pluggable tokenizers, zero dependencies.

The agent reliability stack: fit, guard, snap, vet, cast. One install for all five sibling libraries (token-aware truncation, network-egress firewall, snapshot tests, tool-arg validation, structured-output enforcer).