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+# 2026-02-27 Session Notes
+
+## Research Prompt Chain - Planning & Architecture
+
+Session focused on designing a 5-step research automation chain for a freelance client project. The chain takes a biological mechanism + ingredient list as input, runs through sequential research prompts using MCP-based search (PubMed + Brave Search), and produces a formatted markdown evidence report. Key architectural decision: each of 5 agents processes one step, reading/writing to `tmp/step-N.md` for inter-step handoffs, with final output to `output/[mechanism-slug].md`.
+
+### Architecture Overview
+
+The chain flows: step1-resolver (placeholder resolution) → step2-mechanism (PubMed search) → step3-ingredients (PubMed search) → step4-scorer (ranking, no search) → step5-formatter (compilation, no search). Client provided raw prompt templates, sample inputs, and reference output; implementation wires existing prompts together rather than creating new ones.
+
+### Critical Design Decisions
+
+- **MCP Search Integration**: Agents 2-3 use PubMed MCP tools for real study retrieval; no training-data hallucination. Brave Search as fallback when PubMed insufficient.
+- **Citation Standards**: Global rule enforced across all agents—never cite without real DOI, never fabricate quotes, always verify statistical significance.
+- **Tool Assignments**: Step1 (reasoning only), Steps2-3 (search-enabled), Step4 (Brave fallback only), Step5 (compilation only).
+- **Output Format**: Step agents write full intermediate outputs; orchestrator skill reads previous steps sequentially and maintains clean context.
+
+### File Structure
+
+Project layout organized as: `.claude/` (skills, agents, rules), `prompts/` (5 client-provided templates split into individual files), `samples.md` (input data), `sample-output.md` (reference), `tmp/` (inter-step handoffs, gitignored), `output/` (final reports), plus `HANDOFF.md` (non-technical user guide) and `CLAUDE.md` (project instructions).
+
+### Open Threads
+
+Implementation not yet started—plan phase complete. Next: create 5 agent files, orchestrator skill, split prompts into separate files, configure MCP servers, write rules and handoff docs, then end-to-end test with sample mechanism.
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