research

# Research Session Orchestrator Run a full multi-source research session: classify the domain, dispatch parallel agents, synthesize findings, and output a formatted report. ## Workflow ### Step 1: Classify Domain Run the domain classifier on the topic: ```python from tome.scripts.domain_classifier import classify result = classify(topic) # result.domain, result.triz_depth, result.channel_weights ``` If confidence < 0.6, ask the user to confirm or override the domain classification before proceeding. ### Step 2: Plan Research ```python from tome.scripts.research_planner import plan research_plan = plan(result) # research_plan.channels, research_plan.weights, research_plan.triz_depth ``` ### Step 3: Create Session ```python from tome.session import SessionManager mgr = SessionManager(Path.cwd()) session = mgr.create(topic, result.domain, result.triz_depth, research_plan.channels) ``` ### Step 4: Dispatch Agents Launch research agents in parallel using the Agent tool. Use this mapping: | Channel | Agent Type | Prompt Includes | |---------|-----------|-----------------| | code | `tome:code-searcher` | topic | | discourse | `tome:discourse-scanner` | topic, domain, subreddits | | academic | `tome:literature-reviewer` | topic, domain | | triz | `tome:triz-analyst` | topic, domain, triz_depth | **Rules:** - Always dispatch code and discourse agents - Dispatch academic agent only if "academic" is in research_plan.channels - Dispatch triz agent only if "triz" is in r...