memory-guardian-agnet
by @5rbdmak7f-alt
Agent workspace memory lifecycle management via 10 MCP tools + batch maintenance. Manages MEMORY.md, memory/ directory, meta.json, quality gate, Bayesian dec...
clawhub install memory-guardian-agentπ About This Skill
name: memory-guardian description: > Agent workspace memory lifecycle management via 10 MCP tools + batch maintenance. Manages MEMORY.md, memory/ directory, meta.json, quality gate, Bayesian decay, case lifecycle, and compaction. Use when: (1) Installing or configuring memory-guardian, (2) Running scheduled or on-demand memory maintenance, (3) Diagnosing memory bloat, quality anomalies, or case invalidation, (4) Writing, querying, or archiving memories, (5) Reviewing or retiring judgment cases, (6) Checking quality gate state or L3 confirmations. Triggers on: memory_status, memory_decay, memory_ingest, memory_compact, quality_check, case_query, case_review, run_batch, memory_sync, meta.json, MEMORY.md, memory-guardian.
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 β memory_status first
2. Dry-run before apply β preview destructive operations
3. Default behavior > toggles β workspace defaults from MG_WORKSPACE
4. Write ordering > content correctness β sequence matters
5. Observable but not brittle β signal degradation β WARNING, not crash
6. Single source of truth β 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() β System overview (memory count / gate state / case summary / references integrity)memory_query(type="active", min_score=0.3) β Search memories (keyword/memory_type filter)Write
memory_ingest(content="...", importance="auto", tags=[]) β Create new memorymemory_decay(lambda=0.01, dry_run=false) β Run five-track Bayesian decayAudit
quality_check(layer="all") β Quality gate (retire_rate / similar_case_signal / stale_cases)case_query(filter="frozen") β Query cases (active/frozen/retired/stale/ignored)case_review(case_id, action="retire", origin_type="agent_initiated") β Case operations (active/frozen/retired/unfreeze/ignore)Batch
run_batch(skip_compact=true, dry_run=false, timeout=300) β Full maintenance (includes sync + signal merge)memory_sync(dry_run=true) β Sync file changes β meta.json (auto-run in run_batch)memory_compact(dry_run=true, aggressive=false) β Compact MEMORY.mdWorkflows
New Installation
1. memory_status β 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:
Diagnostics
D1: Memory bloat β memory_compact(dry_run=true) β apply if needed β see compaction.md
D2: Quality anomaly β quality_check(layer="all") β see error_recovery.md
D3: Case invalidation β case_query(filter="stale") β case_review(action="retire"|"active"|"unfreeze") β see case-management.md
Signal Loop (v0.4.6)
Dual-layer access signals feed the decay engine:
access_log.jsonl β agent appends after memory_getAgent 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 [--workspace ]
Commands: status, ingest, bootstrap, snapshot, run, violations, migrate