Rounds Budget

• claude_code_budget_usd (default: $2.00 per diagnosis)
• openai_budget_usd (default: $2.00 per diagnosis)
• daily_budget_limit (default: $100.00)

The daemon scheduler (rounds/adapters/scheduler/daemon.py:209-231) tracks daily spending in-memory and enforces limits during poll cycles.

Implementation

1. Check Current Configuration

Read budget settings from environment or defaults:

# View current budget configuration
grep -E "budget|BUDGET" .env 2>/dev/null || echo "Using defaults from config.py"

# View configuration schema
grep -A 5 "Budget controls" rounds/config.py

2. Query Database for Historical Spending

The SQLite database stores all diagnosis costs in the diagnosis_json field of the signatures table. Extract and sum costs:

# Connect to SQLite and query diagnosis costs
sqlite3 ./data/signatures.db "
SELECT
    COUNT(*) as total_diagnoses,
    SUM(json_extract(diagnosis_json, '$.cost_usd')) as total_spent_usd,
    AVG(json_extract(diagnosis_json, '$.cost_usd')) as avg_cost_per_diagnosis,
    MAX(json_extract(diagnosis_json, '$.cost_usd')) as max_single_diagnosis,
    MIN(json_extract(diagnosis_json, '$.cost_usd')) as min_single_diagnosis
FROM signatures
WHERE diagnosis_json IS NOT NULL;
"

3. View Spending by Service

Break down diagnosis costs by service to identify high-cost areas:

sqlite3 ./data/signatures.db "
SELECT
    service,
    COUNT(*) as diagnoses_count,
    SUM(json_extract(diagnosis_json, '$.cost_usd')) as service_total_usd,
    AVG(json_extract(diagnosis_json, '$.cost_usd')) as avg_cost_usd
FROM signatures
WHERE diagnosis_json IS NOT NULL
GROUP BY service
ORDER BY service_total_usd DESC;
"

4. View Recent Diagnoses with Costs

Show the most recent diagnosed errors and their costs:

sqlite3 ./data/signatures.db "
SELECT
    substr(id, 1, 8) as sig_id,
    service,
    error_type,
    json_extract(diagnosis_json, '$.model') as model,
    json_extract(diagnosis_json, '$.cost_usd') as cost_usd,
    json_extract(diagnosis_json, '$.confidence') as confidence,
    datetime(json_extract(diagnosis_json, '$.diagnosed_at')) as diagnosed_at
FROM signatures
WHERE diagnosis_json IS NOT NULL
ORDER BY json_extract(diagnosis_json, '$.diagnosed_at') DESC
LIMIT 10;
"

5. Calculate Daily Spending (In-Memory)

The daemon scheduler tracks daily spending in-memory (_daily_cost_usd in rounds/adapters/scheduler/daemon.py:38-40). This resets at midnight UTC. To view current daily spending while daemon is running, you would need to:

1. Add a CLI command to expose the scheduler's _daily_cost_usd value
2. Or query recent diagnoses from today:

sqlite3 ./data/signatures.db "
SELECT
    COUNT(*) as today_diagnoses,
    SUM(json_extract(diagnosis_json, '$.cost_usd')) as today_spending_usd
FROM signatures
WHERE diagnosis_json IS NOT NULL
  AND date(json_extract(diagnosis_json, '$.diagnosed_at')) = date('now');
"

6. Budget Enforcement Check

The daemon (rounds/adapters/scheduler/daemon.py:187-207) checks budget limits before each investigation cycle:

• If daily_budget_limit is set (e.g., DAILY_BUDGET_LIMIT=100.0), spending is tracked
• When _daily_cost_usd >= budget_limit, investigation cycles are skipped
• Budget resets at midnight UTC

To verify budget enforcement:

# Check if daemon would skip investigations
# (requires reading daemon logs or adding status endpoint)
grep -E "budget.*exceeded|Daily budget limit" logs/rounds-daemon.log 2>/dev/null || echo "No budget warnings found"

Examples

Example 1: Quick Budget Summary

/rounds-budget
# Output shows:
# - Total diagnoses: 42
# - Total spent: $84.50 USD
# - Avg cost: $2.01 USD
# - Budget limit: $100.00 USD
# - Remaining today: $15.50 USD

Example 2: Detailed Service Breakdown

After running the skill, you'll see:

Service Spending Report:
------------------------
payment-api:     $32.40 (16 diagnoses, avg $2.03)
user-service:    $28.14 (14 diagnoses, avg $2.01)
notification-svc: $24.00 (12 diagnoses, avg $2.00)

Total: $84.54 across 42 diagnoses
Daily Limit: $100.00 (15.46% remaining)

Example 3: Check if Budget is Exceeded

/rounds-budget
# If daily spending exceeds limit:
# ⚠️  BUDGET EXCEEDED: $103.50 / $100.00 (103.5%)
# Investigation cycles are currently paused.

Example 4: Historical Trend Analysis

# After running /rounds-budget, follow up with date-based query:
sqlite3 ./data/signatures.db "
SELECT
    date(json_extract(diagnosis_json, '$.diagnosed_at')) as diagnosis_date,
    COUNT(*) as count,
    SUM(json_extract(diagnosis_json, '$.cost_usd')) as daily_total_usd
FROM signatures
WHERE diagnosis_json IS NOT NULL
GROUP BY diagnosis_date
ORDER BY diagnosis_date DESC
LIMIT 7;
"
# Shows spending trends over the last 7 days

Key Files Referenced

• rounds/config.py:82-101 - Budget configuration (per-diagnosis and daily limits)
• rounds/adapters/scheduler/daemon.py:209-231 - Daily budget tracking and enforcement
• rounds/core/investigator.py:18-22 - BudgetTracker protocol interface
• rounds/adapters/store/sqlite.py:97,425,440 - Diagnosis cost storage in diagnosis_json
• rounds/core/models.py:107 - Diagnosis.cost_usd field
• ./data/signatures.db - SQLite database storing all diagnosis costs

Architecture Context

Budget tracking in rounds follows the hexagonal architecture pattern:

1. Core Domain (rounds/core/investigator.py:18-22) defines the BudgetTracker protocol
2. Adapter Implementation (rounds/adapters/scheduler/daemon.py) implements budget enforcement
3. Persistence (rounds/adapters/store/sqlite.py) stores historical costs in JSON
4. Configuration (rounds/config.py) provides budget limits from environment

The daemon scheduler serves dual purposes:

• Orchestrates poll/investigation cycles
• Tracks daily spending and enforces limits (implements BudgetTracker protocol)

This skill was automatically generated from the rounds codebase architecture.