Enables AI agents to self-report every tool call, token usage, decision, and session grade into a local SQLite store, so users can trace execution, audit reasoning, and see per-session costs in a local dashboard. Also supports proxy mode to intercept and trace MCP tool invocations for agents that cannot self-report.
Enables LLMs to analyze logs by extracting patterns, redacting secrets, and providing token-efficient summaries from files, Docker containers, or journald.
Indexes and searches agent conversation logs from Antigravity and Cursor workspaces, enabling semantic search, token analysis, and benchmarking over local SQLite storage.
Captures and stores console output from any process in SQLite with full-text search, enabling AI assistants to search logs, monitor errors, and analyze multi-process activity through natural language queries.