agent-loop-trace

name	agent-loop-trace
description	Visualize an agent's perceive→think→act loop. Inspects tool calls, latency per step, decision branches, retry patterns. Surfaces bottlenecks. Triggers on "trace agent", "why is agent slow", "agent loop analysis", "what did the agent do".

agent-loop-trace

Workflow

1. Locate agent run logs / transcript.
2. Parse into steps: each step = {perceive (input), think (reasoning), act (tool call), observe (result)}.
3. Compute per-step metrics: latency, tokens in/out, tool used, error?
4. Render timeline + decision tree.
5. Flag patterns: retry loops, redundant tool calls, hallucinated tools, premature termination.

Output

Run: agent_xyz  (total 47s, $0.18, 23 steps)

Step | t(s)| Tokens | Action
  1  | 0.4 | 220/80 | perceive: user prompt
  2  | 2.1 | 280/40 | think: plan 3 steps
  3  | 8.2 | 120/0  | tool: search ✓
  4  | 1.1 | 140/60 | think: refine
  5  | 7.8 | 110/0  | tool: search ✗ (same query)  ← REDUNDANT
  6  | ...

Anti-patterns detected:
  • Same search query twice (steps 3, 5)
  • Long think gap with no progress (steps 11-14)
  • Final answer not grounded in tool results

Reference

"How I use LLMs" / "Deep Dive into LLMs" Karpathy talks