distilllisted

# Distill Methodology Guidelines for automated knowledge extraction and consolidation across memory systems. ## Knowledge Candidate Criteria An insight qualifies as a knowledge candidate when it meets ANY of these: | Criterion | Source | Example | |-----------|--------|---------| | Cross-conversation pattern | 3+ context.md files contain the same insight | "Redis pool exhaustion under SSE load" | | Architectural decision | design.md contains explicit Decision/Rationale section | "Use pgvector for semantic search" | | Recurring gotcha/bug | Keyword match in specs: gotcha, bug, pattern, lesson | "POST 301 redirect strips body" | | Stale reference | File path in memory points to non-existent file | "app/backend/old_module.py" | | Cross-tier duplicate | Same entry in both KNOWLEDGE.md and agent MEMORY.md | Duplicated bullet point | ## Confidence Scoring | Occurrences | Confidence | Tier Recommendation | |-------------|------------|---------------------| | 5+ conversations | 0.5 - 1.0 | shared (KNOWLEDGE.md) | | 3-4 conversations | 0.3 - 0.5 | shared (with review) | | 1-2 conversations | 0.1 - 0.2 | agent-specific MEMORY.md | | Decision section | 0.7 fixed | shared | | Pattern keyword | 0.5 fixed | shared | | Stale reference | 0.9 fixed | cleanup action | ## Tier Routing | Target | When | Path | |--------|------|------| | `shared` | Cross-cutting insight useful to all agents | `.scaffolding/agent-memory/shared/KNOWLEDGE.md` | | `agent:{name}` | Domain-specific to one agent