TL;DR
- An autonomous web-research agent needs a bounded plan, source policy, retrieval loop, and evidence ledger—not an unrestricted browser.
- Separate discovery, page collection, extraction, synthesis, and citation so one bad page does not become a confident answer.
- Give the agent a narrow Nstdata Crawl tool with URL, depth, page, timeout, and output limits.
- Require the agent to stop when evidence is thin, contradictory, or outside the approved scope.
What an autonomous research loop should do
Expose Nstdata Crawl only as a bounded collection tool inside the agent.
An AI agent that researches the web autonomously should turn a question into a small set of testable subquestions, collect sources, extract claims, compare evidence, and return citations with uncertainty. The API-based web-agent research describes why tool calls and browser interaction are different agent designs; production systems should make that boundary explicit.
A safe agent research flow
- Plan: define the question, date window, source types, and stop conditions.
- Discover: search or use known source URLs; keep a bounded queue.
- Collect: call a crawler with explicit page and depth limits.
- Extract: preserve URL, title, fetched time, and content hash with each claim.
- Cross-check: require two independent sources for high-impact claims when practical.
- Synthesize: answer only from accepted evidence and list unresolved conflicts.
The MCP agent guide and RAG guide provide useful Nstdata context; the web-crawling glossary explains why discovery must remain bounded.
