docs(work): add research subagent and refactor alan prompt

docs/work/subagents.md

@@ -6,8 +6,38 @@ Subagents are runtime processes exposed as MCP tools. The canonical prompt text
 
 ## Catalog
 
+### research
+
+**Purpose:** Answer a question by querying both the public web and Robert's Neo4j memory in parallel, then synthesizing one integrated response with conflicts flagged and suggested memory updates surfaced.
+
+**Composition:** `fast.parallel` of three sub-agents:
+- `web_search` — argos
+- `memory_lookup` — neo4j (read-only); framed around work-team node types (clients, opportunities, engagements, decisions, technologies, contacts)
+- `synthesizer` — merges the two reports, flags conflicts, suggests which node type a memory update would belong on
+
+**Tools:** argos, neo4j_cypher
+
+**When to delegate:**
+- Pre-meeting prep on a client or contact — what's already in the graph, plus current public information (recent news, funding, leadership changes)
+- Opportunity qualification where the answer might exist in prior `Decision` or `Technology` nodes AND on the public web
+- "What do we already know about X, and what's the current public information on it?" against the work pipeline
+- When a lead wants memory-aware research without burning its own context on parallel queries
+
+**When NOT to delegate:**
+- Quick web lookups where memory isn't relevant — use argos directly
+- Pure graph queries on a known client or opportunity — query Neo4j directly
+- AWS architecture design questions — use `aws-sa`
+- Deep library/framework/API research — that lives in engineering's `tech_research`. If work needs it regularly, copy it here per the cross-team-reuse convention.
+
+**Prompt:** [prompts/work/subagents/research.md](../../prompts/work/subagents/research.md)
+
+**Runtime:** TBD — copy of engineering's `kottos/agents/research.py` with the work-team memory framing applied. Port to be assigned when wired up.
+
+---
+
 ### aws-sa
 
+
 **Purpose:** AWS cloud architecture design. Selects services, defines how they connect, evaluates trade-offs, estimates costs, and produces architecture diagrams as SVG. Follows the AWS Well-Architected Framework across all six pillars.
 
 **Composition:** Single `fast.agent` with detailed instructions covering Well-Architected principles, SVG diagram production rules, and the requirements-then-design workflow.