Agent Search Budget Controller

A startup deploys a budget controller for their customer support agent. Limits: 10 search calls per customer question, $10/day total, $200/month. Week 1: agent averages 4.2 calls per question, $6.30/day. Week 2: a bug causes the agent to loop on one query, but the per-task limit of 10 calls caps the damage at $0.05 instead of potentially unlimited. Monthly cost: $140, under the $200 budget. Without the controller, the bug alone could have cost $50+ in a single incident.

Agent Search Budget Controller is relevant to Google, Amazon, YouTube, Reddit, TikTok. Scavio provides a unified API to access data from all of these platforms.

AI agents making autonomous tool calls can generate unexpected search API costs. Without budget controls, a research agent investigating a complex topic might make 50+ search calls, costing $0.25 per question. A monitoring agent checking 1,000 keywords might exhaust a monthly budget in a single run. Budget controllers prevent these scenarios. Controller layers: (1) Per-task limit: maximum search calls per user query or task. Typical: 5-15 calls. Prevents single tasks from consuming disproportionate budget. When limit is hit, the agent must synthesize from data already retrieved. (2) Hourly limit: maximum calls per hour across all tasks. Prevents burst usage that could exhaust daily budget. (3) Daily limit: hard cap on daily spend. At $0.005/query with a $5/day limit: 1,000 queries max/day. (4) Monthly limit: aligned with your API plan. Scavio $30/mo plan = 7,000 credits = $35 budget max. Implementation pattern: create a BudgetController class that wraps all search API calls. Before each call, check remaining budget. If budget is exhausted, return a budget-exceeded message that the agent can interpret as 'no more searches available, work with existing data.' Log all calls with timestamps and costs for auditing. Alert thresholds: notify at 50% monthly budget consumed (early warning), 80% (slow down non-critical queries), 95% (critical, only allow essential queries). Use webhook alerts to Slack or email. Common failure modes without budget control: (1) Agent retry loop: query fails, agent retries 100 times. (2) Recursive research: agent searches, finds sub-topics, searches each sub-topic recursively. (3) Parallel monitoring: scheduled job runs before previous job completes, doubling query volume.