research

# research ## Purpose Web research utility. Receives a research question, executes targeted searches, deep-dives into top results, and returns structured findings with sources. Stateless — no memory between calls. ## Calls (outbound) None — pure L3 utility using `WebSearch` and `WebFetch` tools directly. ## Called By (inbound) - `plan` (L2): external knowledge for architecture decisions - `brainstorm` (L2): data for informed ideation - `marketing` (L2): competitor analysis, SEO data - `hallucination-guard` (L3): verify package existence on npm/pypi - `autopsy` (L2): research best practices for legacy patterns - `ba` (L2): research similar products and integrations - `graft` (L2): research source repo patterns before grafting - `mcp-builder` (L2): research MCP standards and existing implementations - `scaffold` (L1): research project templates and best practices ## Execution ### Input ``` research_question: string — what to research focus: string (optional) — narrow the scope (e.g., "security", "performance") ``` ### Step 1 — Formulate Queries Generate 2-3 targeted search queries from the research question. Vary phrasing to cover different angles: - Primary: direct question as search terms - Secondary: "[topic] best practices 2026" or "[topic] vs alternatives" - Tertiary: "[topic] example" or "[topic] tutorial" if implementation detail needed ### Step 2 — Search (Minimum 3 Complementary Sources) <HARD-GATE> Every research conclusion MUST be backed by at minim...