curiositech Cost Optimizer
Tracks cumulative LLM costs across DAG execution and makes real-time decisions to stay within budget: downgrade models, skip optional nodes, or stop early.
When to Use
✅ Use for:
- Setting and enforcing cost budgets for DAG executions
- Real-time cost monitoring during execution
- Deciding when to downgrade model tiers mid-execution
- Identifying which nodes are most expensive and why
- Post-execution cost analysis and optimization recommendations
❌ NOT for:
- Choosing which model to use per node (use
llm-router) - Provider pricing comparisons (static data, not a skill)
- Billing or invoicing features
Budget Enforcement Process
flowchart TD
N[Node about to execute] --> C[Check: spent + estimated_node_cost vs budget]
C --> S{Within budget?}
S -->|Yes, >20% remaining| E[Execute at planned model tier]
S -->|Yes, <20% remaining| W[Execute but downgrade to Tier 1 if possible]
S -->|No| D{Node optional?}
D -->|Yes| SK[Skip node]
D -->|No| H{Human gate available?}
H -->|Yes| A[Ask human: continue over budget?]
H -->|No| ST[Stop execution, return partial results]
Budget Tiers
| Budget Remaining | Action |
|---|---|
| >50% | Execute at planned model tier |
| 20-50% | Log warning. Continue at planned tier. |
| 10-20% | Downgrade remaining Tier 2 nodes to Tier 1 (Haiku) |
| 5-10% | Downgrade ALL remaining nodes to Tier 1. Skip optional nodes. |
| <5% | Stop execution unless next node is critical path |
| 0% | Stop. Return partial results with cost breakdown. |
Cost Estimation Per Node
Before each node executes, estimate its cost:
estimated_cost = (avg_input_tokens × input_price + avg_output_tokens × output_price)
Use historical averages for this skill + model combination. If no history, use defaults:
- Tier 1 (Haiku): ~800 input + 400 output = ~$0.001
- Tier 2 (Sonnet): ~2000 input + 1000 output = ~$0.012
- Tier 3 (Opus): ~3000 input + 1500 output = ~$0.16
Post-Execution Report
cost_report:
total_budget: 0.50
total_spent: 0.37
budget_remaining: 0.13
nodes_executed: 8
nodes_skipped: 1
nodes_downgraded: 2
model_breakdown:
haiku: { calls: 4, cost: 0.004 }
sonnet: { calls: 3, cost: 0.036 }
opus: { calls: 1, cost: 0.33 }
savings_recommendations:
- "Node 'deep-analysis' used Opus ($0.33) but downstream accepted on first try. Try Sonnet next time — potential saving: $0.32"
- "Nodes 'validate-a' and 'validate-b' are sequential but independent. Parallelize to reduce wall-clock time."
Anti-Patterns
No Budget at All
Wrong: Running DAGs without any cost tracking until the API bill arrives. Right: Every DAG execution has a budget, even if generous. Track spend per node.
Aggressive Downgrading
Wrong: Downgrading Opus nodes to Haiku at 50% budget remaining, causing quality failures that trigger expensive retries. Right: Only downgrade when the alternative is stopping execution. Retries cost more than the original model tier.
Ignoring Retries in Cost
Wrong: Budgeting for one attempt per node. Right: Budget for avg_retries × cost_per_attempt. A node with 3 retries on Sonnet costs $0.036, not $0.012.