agent-memory-systems SKILL.md skillA

agent-memory-systems from aicodedecode/awesome-muse-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.

Install it, pinned
mdr add aicodedecode/awesome-muse-skills/agent-memory-systems@git:20260927.806f3e1

Pins git:20260927.806f3e1 in mdr.lock. Pin the fingerprint instead.

Audit grade
A, 17 of 17 checks passed
Kind
SKILL.md skill
Repository
aicodedecode/awesome-muse-skills
Path
skills-imported/agent-memory-systems/SKILL.md
Versions recorded
1
Latest version
git:20260927.806f3e1, committed Sep 27, 2026
Size
2,317 bytes
Repository stars
25
License
MIT

Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stores), and the cognitive architectures that organize them. Key insight: Memory isn't just storage - it's retrieval. A million stored facts mean nothing if you can't find the right one. Chunking, embedding, and retrieval strategies determine whether your agent remembers or forgets. The field is…

Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.

What the file 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 |
…

Read the whole file at its exact version.

How to install

The exact contents, by fingerprint
mdr add aicodedecode/awesome-muse-skills/agent-memory-systems@sha256:c45f6da6e83d7740

The line at the top of this page pins the label git:20260927.806f3e1, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.

Badge

mdr badge

[![mdr](https://markdownregistry.com/badge/art_326lug7xqoit2ncq.svg)](https://markdownregistry.com/a/art_326lug7xqoit2ncq)

4 badge image fetches in 30 days. What the badge shows.

Versions

The registry has recorded 1 version of this file, committed on Sep 27, 2026.

versioncommittedcommitsizeaudit
git:20260927.806f3e1 latest2026-09-27 806f3e1 2,317 BA view

Audit of the latest version

A  17 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (2317 bytes)
  • pass: No zero-width or bidi control characters
  • pass: No instruction hidden inside an HTML comment
  • pass: No link to an exfiltration or paste host
  • pass: No credential-shaped string
  • pass: No instruction to send local credentials anywhere
  • pass: No text hidden with inline styles
  • pass: No prompt-injection phrasing
  • pass: No curl or wget piped into a shell
  • pass: No recursive delete of root, home or parent
  • pass: No instruction to read or print local credentials
  • pass: No base64 blob over 200 characters
  • pass: No link to a raw IP address
  • pass: No script tag

Source

GitHub

aicodedecode/awesome-muse-skills · 25 stars · license MIT · pushed 2026-10-10 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_326lug7xqoit2ncq
GET https://markdownregistry.com/api/v1/resolve?ref=aicodedecode/awesome-muse-skills/agent-memory-systems
GET https://markdownregistry.com/api/v1/blob/c45f6da6e83d7740b91c32e9ba5a7320bbdc4e5c973416af6371b53e599f1dc6

Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.

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