name: agent-health type: workflow description: "Reads production/traces/agent-metrics.jsonl and displays a per-agent performance summary table for the current or a specified session. Highlights agents with high error rates or OPEN circuit breaker state." argument-hint: "[--session <branch>] [--agent <name>] [--since <YYYY-MM-DD>] [--log]" user-invocable: true allowed-tools: Read, Write, Bash effort: 1 when_to_use: "Run at the end of a session, sprint, or after repeated agent failures to identify which agents are struggling. Also useful before dispatching a multi-agent workflow to check circuit breaker states."

Agent Health

Display a performance summary table from production/traces/agent-metrics.jsonl, cross-referenced with production/session-state/circuit-state.json for live circuit breaker states.

Steps

1. Parse arguments

Get current branch: git branch --show-current.

2. Read data sources

Read both files in parallel:

• production/traces/agent-metrics.jsonl — historical metrics per agent per session
• production/session-state/circuit-state.json — live circuit breaker states

If agent-metrics.jsonl contains only the schema header line (no actual entries):

📭 No agent metrics recorded yet for this session.
   Metrics are written when agents use /agent-health --log
   or at the end of a session via /save-state.

Circuit breaker states (live):
[show table from circuit-state.json only]

3. Aggregate metrics

For each agent, compute across the filtered entries:

• total_tasks = tasks_completed + tasks_failed + tasks_blocked
• success_rate = tasks_completed / total_tasks * 100 (0 if no tasks)
• error_rate = latest error_rate field value
• circuit_state = from circuit-state.json (live, not from log)

4. Render health table

🏥 Agent Health Report — session: <branch> · <date range>
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Agent                  Tasks  ✅ Done  ❌ Failed  ⛔ Blocked  Success%  Circuit
──────────────────────────────────────────────────────────────────────────────
backend-developer          8       7          1          0      87.5%   🟢 CLOSED
frontend-developer         5       5          0          0     100.0%   🟢 CLOSED
qa-engineer                  6       4          2          0      66.7%   🟡 HALF-OPEN
data-engineer              2       2          0          0     100.0%   🟢 CLOSED
diagnostics                1       0          1          0       0.0%   🔴 OPEN
──────────────────────────────────────────────────────────────────────────────
TOTAL                     22      18          4          0      81.8%

⚠️  Agents needing attention:
  🔴 diagnostics      — Circuit OPEN · fallback: surface to user
  🟡 qa-engineer        — Circuit HALF-OPEN · 2 failures this session

Circuit state icons:

• 🟢 CLOSED — healthy
• 🟡 HALF-OPEN — recovering, monitor closely
• 🔴 OPEN — bypassed, routed to fallback

Flag agents as needing attention if:

• circuit_state is OPEN or HALF-OPEN
• success_rate < 70%
• tasks_failed >= 2

5. Log snapshot (if --log)

If --log flag was passed, append one entry per active agent to production/traces/agent-metrics.jsonl:

{"date":"<YYYY-MM-DD>","session":"<branch>","agent":"<agent>","tasks_completed":<N>,"tasks_failed":<N>,"tasks_blocked":<N>,"avg_tokens_est":<N>,"error_rate":<0.0-1.0>,"circuit_state":"CLOSED|OPEN|HALF-OPEN","notes":"<optional>"}

Get circuit_state from circuit-state.json. Estimate avg_tokens_est from decision ledger entry count × 800 tokens (rough estimate per entry) if no exact token data is available. Note this is an estimate and mark with _est suffix.

Print after logging:

✅ Metrics snapshot logged → production/traces/agent-metrics.jsonl
   [N] agents recorded · <date>

6. Suggest actions

After the table, if any agents need attention:

💡 Suggested actions:
  • /resume-from <task_id>        — recover failed task checkpoint
  • /trace-history --risk High    — audit high-risk decisions
  • Check circuit-state.json      — update OPEN agents once issue resolved

How metrics get into the file

Agents append entries in two ways:

1. Manual: Run /agent-health --log at end of session
2. Via /save-state: When saving state with a task_id, metrics for the active agent are appended automatically

The file grows one JSON line per agent per session. Use --since to filter to recent sessions and avoid reading stale data from weeks ago.

Quick examples

# Summary for current session
/agent-health

# Check one agent across all time
/agent-health --agent qa-engineer

# Log a fresh snapshot and view it
/agent-health --log

# Review last 7 days
/agent-health --since 2026-04-09