openmemory

A persistent memory manager for coding agents, using OpenMemory to store and retrieve information across conversations. It also keeps a small file-based index as a fallback.

In plain words
What is it for?
It is for saving information the agent should remember, recalling previous context, and removing or maintaining stored memories.
Why use it?
It prevents useful decisions, facts, preferences, and past events from being lost between tasks, while providing rules for updating outdated memories.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/caviraoss/openmemory/docs
Any agent
npx skills add CaviraOSS/OpenMemory --skill docs
Clone the repo
git clone --depth 1 https://github.com/CaviraOSS/OpenMemory

Made for: Claude Code, Codex.

Per session 96 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,987 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00096 $0.01987
Opus 5 $0.00048 $0.00993
Sonnet 5 $0.00019 $0.00397
Haiku 4.5 $0.00010 $0.00199

Measured yesterday against content hash 08063e0c91a6, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

openmemory scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

docs/SKILL.md · 203 lines

How it starts

The opening of the file, as written. The whole thing — 203 lines — stays where its author put it; the contents beside it link to each section on GitHub.

OpenMemory — OpenMemory MCP Operation Playbook

1. Overview

This skill is the operational playbook for OpenMemory (MCP) — a primary persistent memory system; the file-based fallback is a secondary index only (one-line pointers, no full-text copies). Configure project_id based on your workspace (see §4 Step 2).


2. HARD-GATE


3. Flow Router

Trigger Signal Route When
User says "remember this", "save to memory", "store this" — or agent forms a stable conclusion worth persisting SAVE Post-task, or at user request
User says "recall", "what do you remember about", "check memory" — or agent needs historical context before answering QUERY Pre-task, or when context is insufficient
User says "forget this", "delete memory", "clean up memory" — or agent discovers outdated/wrong/duplicated memory MAINTAIN On discovery or user request

4. SAVE Flow (5 Steps)

Step 1 — Classify sector

Content Type Sector Example
Events / incidents that happened episodic "2026-05-20 deployment 回滚"
Facts / knowledge / decisions / preferences semantic "服务 A 依赖 服务 B 的 API v2"
Procedures / methods / rules / constraints procedural "部署前必须运行测试套件"
User emotions / reactions / preferences emotional "用户不喜欢冗长的总结"
Cross-event patterns / insights reflective "部署失败通常与配置缓存有关"

Step 2 — Choose scope

Question YES NO
Is this specific to the current workspace/project? openmemory_store_project (project_id: "{{PROJECT_ID}}") Go to next question
Is this general engineering knowledge? openmemory_store (global) Default to project scope

Read the full file on GitHub · 203 lines

Files

What ships with it

10 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 203 lines · 96 tokens per session scan A 08063e0c91a6

Subscribe to this mod's changes

openmemory is a skill published in the GitHub repository CaviraOSS/OpenMemory (4,476 stars, last pushed yesterday), licensed Apache-2.0. It adds 96 tokens to every session and 1,987 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

reflex-create

Use when the user notices a recurring pattern they want the system to learn ("I keep doing X", "every time Y happens", "make this automatic", "remember to always"), or when explicit phrases like "/reflex-create", "create reflex", "teach yourself" are used. Generates a new SKILL.md file from observed patterns.

terrizoaguimor/celiums-memory · 72 tokens

surface-learnings

Use when the user asks "what have you learned", "what do you remember about me", "show me memory stats", "memory state", "/reflexes", or any variant. Surfaces what the limbic engine has accumulated as patterns, not as a memory dump.

terrizoaguimor/celiums-memory · 60 tokens

context-recovery

Use at the start of every session, and especially after context compaction or a cold restart. Fires as the first action, before engaging with the user's opening message.

terrizoaguimor/celiums-memory · 37 tokens

emotional-calibration

Use when the user's message carries emotional valence — frustration, excitement, exhaustion, urgency, or confusion. Fires whenever tone matters more than information.

terrizoaguimor/celiums-memory · 34 tokens

habituation-check

Use when tempted to repeat the same praise, the same status report, the same explanation, or the same reassurance. Fires as a suppression gate — not all repetition is useful.

terrizoaguimor/celiums-memory · 39 tokens

session-consolidation

Use at the end of any meaningful session — when the user says goodbye, when major work completes, or when context is about to be lost. Fires once, captures the session's essence, prepares for tomorrow.

terrizoaguimor/celiums-memory · 47 tokens