By RohiRIK
Persist and recall project insights, decisions, and gotchas across AI coding sessions using SQLite-backed long-term memory, with automatic context restoration, git history mining, and a graph visualization server.
USE WHEN running schema migrations, scanning memories for secrets, or managing the LTM graph visualization server. Groups migrate | scan | server.
USE WHEN you want to analyze project context before starting work on a task. Calls context + recall, then synthesizes goals, decisions, gotchas, and relevant memories into a pre-task brief.
USE WHEN checking memory health, reviewing project scores, inspecting janitor status, or diagnosing why memories are decaying. Shows health scores, decay summary, activity log, and log health.
USE WHEN recalling past decisions, storing new insights, forgetting stale memories, linking memories, or reviewing pending memory proposals. Groups recall | learn (with optional --save-context) | forget | relate | propose.
USE WHEN setting up LTM for a new project, diagnosing hook or plugin issues, or running first-time setup. Runs the onboarding wizard with doctor checks.
Mines durable engineering memories from git commit diffs and stores them in LTM. Use to onboard a repo, backfill history after enabling gitLearn, or harvest patterns after a sprint. Reads diffs in its own context so raw git output never reaches the main thread.
Expert planning specialist for complex features and refactoring. Use PROACTIVELY when users request feature implementation, architectural changes, or complex refactoring.
Reference for LTM memory commands, context hooks, and DB schema; use when the user mentions learning, recalling, forgetting, relating, or capturing memory, or when a session starts or the project changes.
Mines LTM memories from past git commits. Use when onboarding a repo into LTM, backfilling history after enabling gitLearn, or harvesting patterns after a sprint.
Reference for retrieved patterns and lessons from past sessions; use when prior fixes, gotchas, decisions, or earlier sessions may apply, or when asked what we learned before.
The LTM memory-tool contract โ names, ritual, categories, phase map. USE WHEN recalling, learning, relating, or restoring memory.
Start, stop, or check the LTM graph visualization server; use when the user asks to open, launch, stop, kill, or check graph-server status.
Admin access level
Server config contains admin-level keywords
Uses power tools
Uses Bash, Write, or Edit tools
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Long-Term Memory for AI coding agents โ Claude Code, OpenCode, and Pi
Persistent semantic memory that survives every session, every update, every compaction.
OpenLTM was born as a private memory layer for Claude Code. Today it's fully open source under MIT.
Same engine โ automatic capture, semantic recall, importance-weighted decay, a queryable memory graph โ now yours to read, fork, and extend. What started as one developer's "stop re-explaining my codebase" plugin is now an open foundation for agent memory across Claude Code, OpenCode, and Pi.
@rohirik/openltm-core), thin adapters per host.Migrating from an earlier install? The marketplace is now
RohiRIK/OpenLtmand the plugin isopenltm. Your existing memory database carries over.
Four ideas. No exceptions.
importance: 5 to make something permanent โ everything else ages out naturally.| ๐ Recall | Past decisions, patterns, and gotchas โ before you start work |
| ๐ง Learn | Every session, automatically โ no manual note-taking |
| ๐ Inject | Top context at session start so Claude picks up where it left off |
| โณ Decay | Stale memories fade while critical knowledge lives forever |
| ๐ธ Graph | Traverse relationships between memories for reasoning chains |
| ๐บ Visualize | See your entire memory network in a browser-based explorer |
| โก Vec Recall | Semantic vector (KNN) recall via sqlite-vec; degrades to JS-cosine when unavailable |
| ๐ Extensions | sqlite-vec + Honker (queue/cron/pub-sub) loaded dynamically; graceful fallback without system libsqlite3 |
claude plugin marketplace add https://github.com/RohiRIK/OpenLtm
claude plugin install openltm
Restart Claude Code. That's it. Four Claude Code hooks + one git post-commit hook auto-wire, four commands load, five skills activate, and your openltm.db migrates or creates itself.
bunx @rohirik/openltm-core # auto-detect Claude Code, OpenCode
bunx @rohirik/openltm-core --pi # experimental Pi adapter
bunx @rohirik/openltm-core --dry-run --claude # preview without writing
git clone https://github.com/RohiRIK/OpenLtm ~/Projects/OpenLtm
cd ~/Projects/OpenLtm && bash install.sh
Start a new session. Context is injected at the top automatically.
Then try:
/openltm:memory recall auth โ what do we know about auth in this project?
/openltm:memory learn <insight> โ save something worth keeping
/openltm:health โ memory health + decay summary
/openltm:project init โ set a goal for the current project
That's it. The rest is hooks doing the work.
A dev-team of specialized subagents orchestrated by /buddy, with JSON task tracking.
npx claudepluginhub rohirik/openltm --plugin openltmPersistent memory for AI coding agents. Survives across sessions and compactions.
Persistent memory system for AI coding sessions โ cross-tool memory sharing with 6-dimensional hybrid search
Persistent memory across Claude Code sessions using Cognis
Universal memory runtime โ cross-session cognitive memory for Claude Code. Remembers decisions, patterns, and context across coding sessions.
Auto-capture high-signal coding context into memctl memory
Persistent long-term memory for Claude Code via MCP โ captures coding decisions, bugfixes, and context across sessions. Hybrid FTS5 + TF-IDF search with episode batching. Single SQLite DB, no external services. A lighter, lower-cost alternative to claude-mem (episode batching + a smaller model; cost savings are an internal estimate, not a measured benchmark).