Memory Management

Memory Management (3-Layer Filesystem Engine)

Zero-dependency memory system providing high-speed cognitive continuity across agent sessions without external vector databases or daemon processes.

The 3 Filesystem Layers

1. Layer 1: Runtime Context (Lean Procedural Core)

   • Lean SKILL.md files (target <= 100 lines).
   • Loaded strictly on-demand.
   • Inference Restriction: Historical raw execution traces and multi-page wiki dossiers are barred during active task execution to eliminate context window bloat.

2. Layer 2: Compounding Wiki Layer (Permanent Knowledge)

   • Permanent Markdown documents stored in wiki/ and plugin references/.
   • Contains: domain playbooks, known edge cases, negative constraints, map-debt.md, and evolution-log.md.
   • Knowledge Status Taxonomy: Entries are tagged with explicit confidence (OBSERVED, HYPOTHESIS, CONFIRMED, REJECTED, OPEN).
   • Confidence Decay: Knowledge not re-verified within 30 days decays from CONFIRMED to OBSERVED.
   • Asymmetric Persistence Rule: When an evolution attempt fails, code mutations are rolled back, but wiki insights, edge-case discoveries, and failure logs are NEVER rolled back.

3. Layer 3: Safe Audit Layer (Append-Only Manifests)

   • Stored in .agent/learning/traces/cycle_manifests.jsonl.
   • Tracked audit log capturing event sequences, hashes, exit codes, and affected paths (zero raw terminal text or credentials).
   • Audited exclusively via verify_evolution_receipt.py.

Standardized Retrieval Protocol

All memory lookups use native filesystem tools:

1. Targeted Exact Match: rg "<symbol-or-pattern>" <dir> or grep_search.
2. Playbook Inspection: Direct file read of references/<topic>-playbook.md or wiki/<topic>.md.
3. Map Debt Audit: Scan references/map-debt.md for existing open friction items before starting tasks.