memory-guardian-agnet

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通过10个MCP工具及批量维护实现代理工作空间内存生命周期管理,负责MEMORY.md、memory/目录、meta.json、质量门及贝叶斯决策等。

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skillhub install clawhub_5rbdmak7f-alt/memory-guardian-agent

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memory-guardian

Workspace memory lifecycle system. Dual-layer Bayesian decay + four-state quality gate + case lifecycle + compaction.

Design Principles

  1. Check status before any write — memory_status first
  2. Dry-run before apply — preview destructive operations
  3. Default behavior > toggles — workspace defaults from MG_WORKSPACE
  4. Write ordering > content correctness — sequence matters
  5. Observable but not brittle — signal degradation → WARNING, not crash
  6. Single source of truth — all defaults in mg_schema/meta_defaults.py

MCP Tools (10)

workspace defaults from MG_WORKSPACE env var; only non-default params listed.

Query
- memory_status() — System overview (memory count / gate state / case summary / references integrity)
- memory_query(type="active", min_score=0.3) — Search memories (keyword/memory_type filter)

Write
- memory_ingest(content="...", importance="auto", tags=[]) — Create new memory
- memory_decay(lambda=0.01, dry_run=false) — Run five-track Bayesian decay

Audit
- quality_check(layer="all") — Quality gate (retire_rate / similar_case_signal / stale_cases)
- case_query(filter="frozen") — Query cases (active/frozen/retired/stale/ignored)
- case_review(case_id, action="retire", origin_type="agent_initiated") — Case operations (active/frozen/retired/unfreeze/ignore)

Batch
- run_batch(skip_compact=true, dry_run=false, timeout=300) — Full maintenance (includes sync + signal merge)
- memory_sync(dry_run=true) — Sync file changes → meta.json (auto-run in run_batch)
- memory_compact(dry_run=true, aggressive=false) — Compact MEMORY.md

Workflows

New Installation

  1. memory_status → confirm references.complete: true
  2. If false, create missing files per the missing list, re-verify
  3. Create cron task (see signal-loop.md for cron template)
  4. Manually trigger once to verify

Daily Maintenance (cron)

run_batch(skip_compact=true) runs automatically. Includes:
- memory_sync (incremental file scan)
- Signal merge (access_log + cron inference)
- Decay + quality gate check
- Compact triggers only when MEMORY.md > 15KB

Diagnostics

D1: Memory bloat → memory_compact(dry_run=true) → apply if needed → see compaction.md

D2: Quality anomaly → quality_check(layer="all") → see error_recovery.md

D3: Case invalidation → case_query(filter="stale") → case_review(action="retire"|"active"|"unfreeze") → see case-management.md

Signal Loop (v0.4.6)

Dual-layer access signals feed the decay engine:
- Layer 1 (weight 1.0): access_log.jsonl — agent appends after memory_get
- Layer 2 (weight 0.5): cron keyword inference from daily notes
- Health check auto-degrades to Layer 2 if access_log stale > 24h

Agent must append to access_log.jsonl after each memory_get call. See signal-loop.md for integration code.

References

Load on demand per scenario:

CLI Fallback

When MCP unavailable, CLI path relative to skill dir:

python3 scripts/memory_guardian.py <command> [--workspace <path>]

Commands: status, ingest, bootstrap, snapshot, run, violations, migrate

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