Agent Search Budget

The research agent hit its 25-query per-task budget while investigating competitor pricing. It returned partial findings covering 4 of 6 competitors and flagged that DataForSEO and Bright Data pricing was not yet researched, allowing the user to approve additional budget.

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

AI agents with unrestricted search API access can burn through thousands of credits in minutes through query loops, redundant searches, or overly broad research strategies. Agent search budgets are the primary cost control mechanism. Budget levels operate at three tiers: per-task (maximum credits for one research question, typically 10-50 queries), per-session (maximum credits across all tasks in one agent run, typically 100-500), and per-period (daily or monthly hard cap, typically 1,000-50,000). Implementation requires credit tracking middleware that intercepts every search API call. Example budget configuration: ```typescript const searchBudget = { perTask: 25, // max 25 queries per research question perSession: 200, // max 200 queries per agent run dailyCap: 2000, // max 2,000 queries per day alertAt: 0.8, // alert at 80% consumption action: 'degrade' // 'stop' | 'degrade' | 'alert' }; ``` The 'degrade' action is often better than 'stop': when approaching budget limits, the agent switches from live search to cached results, reduces query breadth, or returns partial findings with a disclosure that budget constraints limited research depth. Cost examples at different budget levels: conservative (25 queries/task at $0.005 = $0.125/task), moderate (100 queries/task = $0.50/task), aggressive (500 queries/task = $2.50/task). For a team running 100 research tasks daily, the difference between conservative and aggressive budgets is $12.50 vs $250/day. Budget optimization strategies: cache search results for 1-24 hours depending on data freshness needs, deduplicate queries across concurrent agent sessions, pre-compute common queries in batch mode (cheaper via DataForSEO queue at $0.0006), and implement query quality scoring that rejects overly broad or redundant searches before they execute.