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[Gastown] PR 17: Agent CVs & Performance Analytics #224

@jrf0110

Description

@jrf0110

Parent: #204 | Phase 3: Multi-Rig + Scaling

No major architectural changes — Agent Identity DO accumulates data from DO RPCs regardless of execution model.

Goal

Build the structured work ledger for agent performance tracking.

Agent Identity DO

Each agent gets a persistent Durable Object that accumulates:

  • Bead closures (type, time, quality signal from refinery)
  • Molecule step completions
  • Convoy participations
  • Escalation history
  • Session count/duration
  • Model used per session

Dashboard Views

  • Agent performance cards: beads closed, avg time to close, quality rate (refinery pass rate)
  • Model comparison: same work type with different models → which performs better
  • Cost per bead: LLM usage from gateway, attributed to agent

Agent Identity DO Schema

CREATE TABLE work_log (
  id TEXT PRIMARY KEY,
  bead_id TEXT NOT NULL,
  bead_type TEXT NOT NULL,
  rig_id TEXT NOT NULL,
  convoy_id TEXT,
  started_at TEXT NOT NULL,
  completed_at TEXT,
  quality_signal TEXT,        -- 'passed', 'rework_requested', 'failed'
  model TEXT NOT NULL,
  token_usage INTEGER,
  cost_cents INTEGER
);

CREATE TABLE escalation_log (
  id TEXT PRIMARY KEY,
  bead_id TEXT NOT NULL,
  severity TEXT NOT NULL,
  category TEXT,
  created_at TEXT NOT NULL
);

Dependencies

  • PR 1 (Rig DO)
  • PR 9 (Town DO)
  • PR 12 (Refinery — quality signals)

Acceptance Criteria

  • Agent Identity DO with work log and escalation log
  • Automatic logging on bead close, escalation, session events
  • Agent performance card component
  • Model comparison view
  • Cost attribution per agent/bead

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    P3Backlog / futuregt:coreReconciler, state machine, bead lifecycle, convoy flow

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