agent-memory-systems

agent-memory-systems is a skill for Claude Code, Codex from cgyudistira/agentkit. It costs 100 tokens per session (486 once invoked), scanned A, a copy of agent-memory-systems, MIT.

A guide to designing memory for AI agents, including short-term conversation context and long-term searchable storage. It focuses on storing useful information and retrieving the right information when needed.

In plain words
What is it for?
Use it when planning agent memory, selecting a vector database, organizing documents into searchable chunks, or deciding between working, episodic, semantic, and procedural memory.
Why use it?
An agent that forgets or gives inconsistent answers may be retrieving the wrong information rather than simply lacking storage. Choosing memory types, document chunks, and retrieval methods helps address that problem.

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/cgyudistira/agentkit/agent-memory-systems
Any agent
npx skills add cgyudistira/agentkit --skill agent-memory-systems
Clone the repo
git clone --depth 1 https://github.com/cgyudistira/agentkit

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for agent-memory-systems

README.md
[![agentmods](https://agentmods.dev/badge/skills/cgyudistira/agentkit/agent-memory-systems.svg)](https://agentmods.dev/skills/cgyudistira/agentkit/agent-memory-systems)
Your own site
<a href="https://agentmods.dev/skills/cgyudistira/agentkit/agent-memory-systems"><img src="https://agentmods.dev/badge/skills/cgyudistira/agentkit/agent-memory-systems.svg" alt="Measured on agentmods" height="20"></a>
Per session 100 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 486 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 100% copy Near-identical to another mod 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 $0.00100 $0.00486
Opus 5 $0.00050 $0.00243
Sonnet 5 $0.00020 $0.00097
Haiku 4.5 $0.00010 $0.00049

Measured 4d ago against content hash c45f6da6e83d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

agent-memory-systems 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 4d ago.

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.

Origin

This is a copy

100% identical to agent-memory-systems — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

templates/skills/agent-memory-systems/SKILL.md · 68 lines

What it actually says

Agent Memory Systems

You are a cognitive architect who understands that memory makes agents intelligent. You've built memory systems for agents handling millions of interactions. You know that the hard part isn't storing - it's retrieving the right memory at the right time.

Your core insight: Memory failures look like intelligence failures. When an agent "forgets" or gives inconsistent answers, it's almost always a retrieval problem, not a storage problem. You obsess over chunking strategies, embedding quality, and

Capabilities

  • agent-memory
  • long-term-memory
  • short-term-memory
  • working-memory
  • episodic-memory
  • semantic-memory
  • procedural-memory
  • memory-retrieval
  • memory-formation
  • memory-decay

Patterns

Memory Type Architecture

Choosing the right memory type for different information

Vector Store Selection Pattern

Choosing the right vector database for your use case

Chunking Strategy Pattern

Breaking documents into retrievable chunks

Anti-Patterns

❌ Store Everything Forever

❌ Chunk Without Testing Retrieval

❌ Single Memory Type for All Data

⚠️ Sharp Edges

Issue Severity Solution
Issue critical ## Contextual Chunking (Anthropic's approach)
Issue high ## Test different sizes
Issue high ## Always filter by metadata first
Issue high ## Add temporal scoring
Issue medium ## Detect conflicts on storage
Issue medium ## Budget tokens for different memory types
Issue medium ## Track embedding model in metadata

Works well with: autonomous-agents, multi-agent-orchestration, llm-architect, agent-tool-builder

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. 4d ago First seen · 68 lines · 100 tokens per session scan A c45f6da6e83d

Subscribe to this mod's changes

agent-memory-systems is a skill published in the GitHub repository cgyudistira/agentkit (2 stars, last pushed 6mo ago), licensed MIT. It adds 100 tokens to every session and 486 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to agent-memory-systems, differing in 0 lines, and is treated as a copy.

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