docs(plans): add openclaw analysis and rollout checklists

2026-02-12 22:47:28 -08:00
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+# Phase 3 PR #1 Checklist: Adaptive Memory Injection and Compaction Weighting
+
+Created: 2026-02-12
+Owner: Flynn core
+Status: ready to implement
+
+## Goal
+
+Improve memory usefulness and compaction quality by injecting relevant memory context adaptively and preserving high-value turns during compaction.
+
+## Scope
+
+In scope:
+- adaptive memory relevance scoring
+- configurable memory injection strategy
+- compaction weighting for important turns (tool outcomes, corrections, preferences)
+- tests and perf guardrails
+
+Out of scope:
+- new vector backend work
+- UI controls for weighting
+
+## Files
+
+New:
+- `src/memory/adaptive.ts`
+- `src/memory/adaptive.test.ts`
+- `src/context/weighting.ts`
+- `src/context/weighting.test.ts`
+
+Modified:
+- `src/backends/native/orchestrator.ts`
+- `src/context/compaction.ts`
+- `src/memory/store.ts`
+- `src/config/schema.ts`
+
+## Implementation Steps
+
+1. Add adaptive memory scorer:
+   - keyword overlap with recent turns
+   - recency weighting
+   - token budget clipping
+2. Add config flags:
+   - `memory.injection_strategy` (`all|recent|adaptive`)
+   - `memory.max_injection_tokens`
+   - `compaction.importance_threshold`
+3. Integrate adaptive injector in orchestrator memory injection path.
+4. Add compaction message weighting and selection algorithm.
+5. Ensure fallback to existing behavior on errors/timeouts.
+6. Add tests for relevance selection and weighted compaction ordering.
+
+## Validation Commands
+
+```bash
+pnpm typecheck
+pnpm test:run src/memory/adaptive.test.ts
+pnpm test:run src/context/weighting.test.ts
+pnpm test:run src/context/compaction.test.ts
+pnpm test:run src/backends/native/orchestrator.test.ts
+pnpm test:run
+pnpm lint
+pnpm build
+```
+
+## Acceptance Criteria
+
+- Adaptive mode injects fewer but more relevant memory snippets.
+- Compaction preserves high-importance turns over low-value chatter.
+- Token budgets are respected consistently.
+- Existing behavior preserved when adaptive features disabled.
+- No measurable latency regression beyond agreed budget.
+
+## Risks
+
+- Relevance scoring false positives/negatives.
+  - Mitigation: conservative scoring + extensive fixtures.
+- Added latency in hot path.
+  - Mitigation: bounded scoring time and fallback mode.
+
+## Commit Message
+
+`feat(memory): add adaptive injection and weighted compaction`