Inter-Agent Coordination Tracker
Track handoff quality, context completeness, and collaboration patterns between AI agents.
Overview
When one AI agent spawns another to handle a subtask, the coordination tracker measures handoff duration, context quality (Complete/Partial/Incomplete), and rework rate. It detects anti-patterns like context loss, circular delegation, and premature escalation, then generates daily coordination reports.
How It Works
A daily job analyzes session logs to identify spawn events (one agent launching another). It assesses context quality by checking for project references, clear goals, and adequate detail. It calculates average handoff time, rework frequency (same task re-attempted), and flags anti-patterns. Results are written to coordination-YYYY-MM.jsonl with daily summaries.
Tools Used
Outcome
Identified 4 instances of context loss where the receiving agent had to ask clarifying questions. Reduced average handoff time from 8 minutes to 3 minutes by improving context templates. Caught 2 cases of circular delegation before they became blockers.