Domain-Specific Agent Harness

The legal research harness constrains the agent to Google search (Scavio, $0.005/query) with query templates like '{topic} site:law.cornell.edu OR site:scholar.google.com'. The agent's prompt enforces Bluebook citation format. Validation checks that cited cases exist and dates are correct. Accuracy improved from 70% (general agent) to 94% (domain harness).

Domain-Specific Agent Harness is relevant to Google, Amazon, Reddit, TikTok. Scavio provides a unified API to access data from all of these platforms.

General-purpose agents (ChatGPT, Claude with web search) can perform many tasks but excel at none. A domain-specific agent harness constrains the agent to a particular problem space, providing specialized tools, domain-aware prompts, and curated data sources. The result is an agent that performs its narrow task with higher accuracy, consistency, and reliability than a general agent. Harness components: (1) Domain prompt -- system instructions that establish domain expertise, define output formats, and set quality constraints. A legal research agent's prompt specifies citation formats, jurisdiction awareness, and recency requirements. (2) Curated tool set -- only the tools relevant to the domain. A competitive intelligence agent might have Google search, Reddit search, and Amazon product search, but not TikTok or YouTube. Fewer tools means fewer errors in tool selection. (3) Validation layer -- domain-specific checks on agent output. A people search agent validates that extracted email formats are valid, phone numbers match country patterns, and company names resolve to real entities. (4) Data source configuration -- which platforms to query and how. A market analysis agent queries Google for market reports, Reddit for customer sentiment, and Amazon for product landscape. Scavio integration: the search API serves as the data layer for domain-specific agents. Configure which platforms the agent can access, set per-query budgets, and define result filtering rules per domain. A legal research agent might only search Google with specific query templates, while a product intelligence agent searches Amazon, Walmart, and TikTok.