ALwrity/docs/flat_file_context/STEP3_FLAT_FILE_CONTEXT_DESIGN.md

Step 3 Flat File Context Design (Research Preferences + Competitors)

Intent

Provide agent-ready Step 3 context with compact summaries for routing plus full payload for deep analysis.

Storage location

• workspace/workspace_<safe_user_id>/agent_context/step3_research_preferences.json

Why this matters for agents

Step 3 is the bridge from website understanding (Step 2) to competitive strategy and research execution. Agents need this file to understand:

• depth and quality preference constraints,
• factuality constraints,
• content-type priorities,
• competitor landscape and industry context.

Document-context block

Every context file should include machine-readable document metadata to orient agents quickly:

• audience (ai_agents)
• purpose (fast_context_retrieval)
• journey stage (onboarding_step_3)
• retrieval contract and fallback order
• context-window guidance (size budget + summary-first policy)

Minimal Step 3 data groups

• research config: depth/content types/auto/factual
• inherited style profile (if present): writing style, target audience, recommended settings
• competitors: domain/url/title/relevance highlights
• industry context: compact market framing text
• traceability: source payload and timestamps

Agent usage policy

1. Start with agent_summary.quick_facts and retrieval_hints.
2. Use competitor summary before opening full competitor objects.
3. Read full data only for tasks requiring strict evidence/fields.
4. Fall back to DB, then SIF semantic if missing or stale.

Related-document navigation

Agents can consult context_manifest.json to discover linked context files and traverse only the required documents for the task.