Overview
Agent Journal captures the behavioral traces that make agent research possible. Every tool call, state transition, and decision point is logged in a structured format that feeds directly into Markov chain analysis and behavioral fingerprinting.What It Captures
- Tool-call sequences — Ordered trace of every tool invocation
- State transitions — Movement between the 9-state taxonomy (ORIENT, READ, EDIT, BUILD, TEST, etc.)
- Timing data — Duration per state, time-per-intent analysis
- Decision metadata — What the agent considered vs. what it chose
Why It Matters
Without structured traces, agent behavior is a black box. Agent Journal transforms agent runs into analyzable data — enabling Markov fingerprinting, loop detection, and cross-variant behavioral comparison.Quick Links
Methodology
How traces become Markov chains — the analysis pipeline
Feeds Into
- Code Coverage v1 — First Markov analysis from captured traces
- Code Coverage v2 — Refined 9-state taxonomy