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Trusty Memory

  • 5 installs
  • 145 repo stars
  • Updated July 27, 2026
  • bobmatnyc/claude-mpm

trusty-memory is a skill that documents a persistent memory-palace system with hierarchical storage, progressive retrieval, and a temporal knowledge graph for cross-session agent context.

About

This skill documents trusty-memory, a persistent memory system that organizes context across sessions using a memory-palace metaphor with hierarchical storage and progressive retrieval layers L0-L3. It exposes MCP tools to remember, recall, and forget drawers and to assert and query knowledge-graph triples. A developer uses it to store decisions, learnings, and relationships so an agent can recall them in later sessions.

  • Persistent memory palace with hierarchical storage (palace/wing/room/closet/drawer)
  • Progressive retrieval layers L0-L3 with memory_recall and memory_recall_deep
  • Temporal knowledge graph via kg_assert and kg_query for cross-session context

Trusty Memory by the numbers

  • 5 all-time installs (skills.sh)
  • Ranked #13,046 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
  • Data as of Aug 2, 2026 (Skillselion catalog sync)
At a glance

trusty-memory capabilities & compatibility

Capabilities
trusty search
Use cases
memory · orchestration
Pricing
Free
From the docs

What trusty-memory says it does

Persistent memory system using the **Memory Palace** metaphor for organizing context across sessions.
SKILL.md
**Always try `memory_recall` first.** Escalate to `memory_recall_deep` only if results are insufficient.
SKILL.md
**Do NOT use for**: ephemeral scratch notes, code snippets (use trusty-search), or content that belongs in source files.
SKILL.md
npx skills add https://github.com/bobmatnyc/claude-mpm --skill trusty-memory

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Listed on Skillselion
Installs5
repo stars145
Last updatedJuly 27, 2026
Repositorybobmatnyc/claude-mpm

What it does

Store and recall cross-session context and knowledge-graph facts for a coding agent.

Who is it for?

Storing architectural decisions, learnings, gotchas, and entity relationships an agent needs to recall across sessions.

Skip if: Ephemeral scratch notes, code snippets (use trusty-search), or content that belongs in source files.

When should I use this skill?

At session start to recall context, at decision moments to store choices, and at session end to persist outcomes.

What you get

Persisted, progressively-retrievable memory and a queryable knowledge graph across sessions.

By the numbers

  • Four progressive retrieval layers L0-L3
  • Nine room types from Backend to General
  • Replaces mcp__kuzu-memory__* tools

Files

SKILL.mdMarkdownGitHub ↗

trusty-memory

Persistent memory system using the Memory Palace metaphor for organizing context across sessions. Replaces mcp__kuzu-memory__* tools.

When to Use

  • Session start: Recall relevant context for the current task
  • Decision moments: Store key architectural/design decisions
  • Learning capture: Remember new patterns, conventions, gotchas discovered
  • Relationship tracking: Assert facts in the knowledge graph (X depends on Y, A replaces B)
  • Session end: Persist outcomes and next steps

Do NOT use for: ephemeral scratch notes, code snippets (use trusty-search), or content that belongs in source files.

Architecture

Palace (project)     e.g. "claude-mpm"
  └── Wing (area)    e.g. "Backend"
        └── Room     e.g. "Backend", "Frontend", "Testing", "Planning",
                          "Documentation", "Research", "Configuration",
                          "Meetings", "General"
              └── Closet (sub-category)
                    └── Drawer (memory item: uuid, content, tags, importance)

Progressive Retrieval Layers

LayerTokensWhenTrigger
L0~100AlwaysIdentity / project context auto-loaded
L1~800AlwaysTop-15 drawers by importance auto-loaded
L2variableOn topic matchmemory_recall — metadata-filtered vector search
L3exhaustiveExplicitmemory_recall_deep — full HNSW deep search

Always try `memory_recall` first. Escalate to memory_recall_deep only if results are insufficient.

Tool Reference

Retrieval

`memory_recall` — Fast progressive retrieval (L0+L1+L2). Use this first.

mcp__trusty-memory__memory_recall(
  query="how does the migration registry work",
  room="Backend",        # optional filter
  limit=10               # optional
)

`memory_recall_deep` — Full HNSW deep search (L3). Use when memory_recall insufficient.

mcp__trusty-memory__memory_recall_deep(
  query="rare edge case in hook dispatcher",
  limit=20
)

`memory_list` — Browse drawers by room/tag (no semantic query).

mcp__trusty-memory__memory_list(room="Planning", tag="release-workflow")

Storage

`memory_remember` — Store a drawer.

mcp__trusty-memory__memory_remember(
  content="The migration runner uses run_pending_migrations() at startup; state in ~/.claude-mpm/migrations.json",
  room="Backend",
  tags=["migrations", "startup"],
  importance=0.8         # 0.0-1.0; higher = more likely to appear in L1
)

`memory_forget` — Delete by UUID.

mcp__trusty-memory__memory_forget(drawer_id="<uuid>")

Palace Management

mcp__trusty-memory__palace_list()
mcp__trusty-memory__palace_info(palace="claude-mpm")
mcp__trusty-memory__palace_create(name="new-project")

Knowledge Graph (temporal triples)

`kg_assert` — Assert a (subject, predicate, object) fact.

mcp__trusty-memory__kg_assert(
  subject="trusty-memory",
  predicate="replaces",
  object="kuzu-memory"
)

`kg_query` — Query triples for a subject.

mcp__trusty-memory__kg_query(subject="trusty-memory")

Room Type Selection

RoomUse For
BackendServer-side logic, APIs, services, data layer
FrontendUI, components, styling, client-state
TestingTest patterns, fixtures, flaky test notes, coverage decisions
PlanningRoadmaps, architectural decisions, ticket plans
DocumentationDoc conventions, README structure, public API docs
ResearchInvestigations, spike findings, library evaluations
ConfigurationBuild setup, env vars, deploy config, tooling
MeetingsDecisions from sync calls, action items
GeneralCross-cutting concerns, miscellaneous

When unsure, prefer the most-specific room. Tags handle the rest.

KG Triple Patterns

Use consistent predicates for queryable graphs:

PredicateExample
replaces(trusty-memory, replaces, kuzu-memory)
depends_on(release-publish, depends_on, gh-account-bobmatnyc)
implements(migration_runner, implements, run_pending_migrations)
documented_in(release_workflow, documented_in, CLAUDE.md)
owned_by(planner-agent, owned_by, .claude/agents/planner.md)
version_of(6.2.67, version_of, claude-mpm)
triggers(SessionStart, triggers, model_tier_hook)

Workflow Protocols

Session Start Protocol

1. Auto-loaded: L0 identity + L1 top-15 drawers appear in context automatically. 2. Targeted recall: For task-specific context:

   memory_recall(query="<current task domain>", limit=10)

3. Check KG for relevant entity relationships:

   kg_query(subject="<entity being modified>")

Session End Protocol

For each significant outcome, persist it:

1. Decisionsmemory_remember with high importance (0.7-0.9)

   memory_remember(
     content="Decided to consolidate hook scripts under claude-hook-fast.sh; old per-event scripts deprecated",
     room="Backend",
     tags=["hooks", "decision"],
     importance=0.85
   )

2. Relationshipskg_assert

   kg_assert(subject="claude-hook-fast.sh", predicate="replaces", object="per-event-hook-scripts")

3. Gotchas / learningsmemory_remember with tags for discoverability

   memory_remember(
     content="release-publish requires `claude-mpm gh switch` to bobmatnyc first; bob-duetto account causes auth failures",
     room="Configuration",
     tags=["release", "gotcha", "github-auth"],
     importance=0.9
   )

Recall vs Recall-Deep Decision

SituationUse
Standard context lookupmemory_recall
Top-N relevant results enoughmemory_recall
memory_recall returned <3 hitsmemory_recall_deep
Investigating obscure / rare topicmemory_recall_deep
Need exhaustive coverage of a conceptmemory_recall_deep

Importance Scoring

ScoreType
0.9-1.0Critical: release gotchas, security constraints, hard rules
0.7-0.9Architectural decisions, major patterns
0.5-0.7Useful conventions, common patterns
0.3-0.5Project trivia, minor preferences
0.0-0.3Ephemeral, rarely-useful

L1 surfaces the top 15 by importance — score accordingly.

Migration from kuzu-memory

OldNew
mcp__kuzu-memory__kuzu_recallmcp__trusty-memory__memory_recall
mcp__kuzu-memory__kuzu_learnmcp__trusty-memory__memory_remember
mcp__kuzu-memory__kuzu_remembermcp__trusty-memory__memory_remember
mcp__kuzu-memory__kuzu_project_contextAuto-loaded via L0
mcp__kuzu-memory__kuzu_statsmcp__trusty-memory__palace_info

Integration with trusty-search

Common pattern: search → understand → remember.

# 1. Find code with trusty-search
search_code(query="migration runner", query_type="Definition")

# 2. After investigating, persist the learning
memory_remember(
  content="Migration runner pattern: registry.py registers each migrate_*.py module; run_pending_migrations iterates by version",
  room="Backend",
  tags=["migrations", "pattern"],
  importance=0.75
)

Best Practices

  • Be specific: "Release workflow requires bobmatnyc gh account" beats "Check gh account before releasing"
  • Include WHY: Decision rationale beats decision alone
  • Tag generously: Tags enable cross-room discovery
  • Use KG for relationships: Don't bury "X replaces Y" in prose — assert it
  • Update over duplicate: Forget stale drawers when superseded
  • Prefer recall over recall_deep: Save the expensive call for when you need it

Related skills

FAQ

What are the retrieval layers?

L0 identity (~100 tokens) and L1 top-15 drawers (~800 tokens) auto-load; L2 is memory_recall for topic matches; L3 is memory_recall_deep for exhaustive HNSW search.

When should I not use trusty-memory?

For ephemeral scratch notes, code snippets (use trusty-search), or content that belongs in source files.

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