Agentic Search Budget

A LangChain agent processing 50 research tasks per day with a 20-credit budget per task stays within 1,000 credits/day ($5 at Scavio rates), vs an uncapped agent that used 4,200 credits in the first test run.

Agentic Search Budget is relevant to google, amazon, tiktok. Scavio provides a unified API to access data from all of these platforms.

At 1,000 queries per day, search API costs vary sharply by provider. Scavio charges $0.005 per credit, putting 1k daily queries at $5/day ($150/mo). SerpAPI costs $0.025 per query on its $25/1k plan, or $750/mo at the same volume. Serper at $50/mo for 500k queries drops cost to $0.0001 each, but requires upfront commitment. Without a budget cap, a looping agent can exhaust a monthly allowance in hours. Implementing a budget in code is straightforward. Track cumulative credits before each tool call and raise a BudgetExceededError when the threshold is hit. Most agent frameworks support pre-tool hooks for this: LangChain's before_tool callback, LlamaIndex's tool wrapper, or a simple counter in a CrewAI tool class. A practical starting point is setting the session budget to 10-20% of the daily credit pool, then adjusting based on observed agent behavior. Agents that search speculatively (hedging retrieval) consume 3-5x more credits than agents with explicit search-before-answer rules. Budget enforcement surfaces this waste immediately.