Research Agent

Autonomous research agent that plans, searches across the web, synthesizes findings, and returns a structured markdown report with citations and (optionally) charts. Use it when the user's question requires consulting multiple sources and producing a readable artifact — not for quick factual lookups.

When to use

• Market scans, literature reviews, competitive analyses, technology surveys
• Multi-section reports that need headings, bullet lists, and citations
• Questions where the user explicitly wants a report, briefing, or write-up
• Tasks that benefit from a chart or two derived from the researched numbers

When NOT to use

• A single factual answer that one wikipedia_search or google_web_search call would resolve — use those tools directly
• Code-related tasks → use the code-agent skill
• Browser automation on a specific site → use the browser-automation skill

How to invoke

Call the research_agent tool with a single plan argument. The plan is free-form prose; include:

• Objectives — what the user is trying to learn or decide
• Topics — the specific angles / subtopics to cover
• Structure — the section layout you want in the final report

Example:

research_agent(plan="""
Research Plan: AI Code Assistant Market 2026

Objectives:
- Current market size and growth trends
- Leading products and differentiators
- Enterprise adoption barriers

Topics:
1. Global market statistics and forecasts
2. Top products (Copilot, Cursor, Claude Code, etc.) and positioning
3. Pricing models and enterprise SKUs
4. Security/compliance concerns raised by buyers

Structure:
- Executive Summary (3-5 bullets)
- Market Overview
- Product Landscape
- Enterprise Adoption
- Outlook
""")

The agent streams research_step progress events as it works. The final result is a markdown report saved as a research artifact in the canvas.

Output

• Markdown report with #/## headings, bullet lists, and inline citations
• Any charts the agent generated are embedded in the markdown
• The full report is also persisted as an artifacts entry so the user can open it from the canvas

Guidelines for the orchestrator

• Don't fabricate the plan — use the user's own words and just structure them into objectives/topics/structure. If the user only gave a one-line request, expand it into 2-3 objectives but stay true to intent.
• One research_agent call per user request. Don't fan out multiple parallel calls.
• If the user asks a follow-up ("add a section on X", "dig deeper into Y"), call research_agent again with an updated plan — the agent itself does not have persistent memory across calls.
• After the tool returns, do NOT restate the whole report in chat. The report is already rendered as an artifact; a 1-2 sentence summary pointing the user to the canvas is enough.