memory-retrieve

A focused memory loader that reveals saved knowledge in three stages, from broad pointers to the details needed for a task. It is designed to load only relevant information rather than an entire memory collection.

In plain words
What is it for?
Use it while preparing a task that depends on past decisions, project facts, or other stored memory.
Why use it?
It reduces unnecessary context and helps keep important task information available. It also keeps durable saved knowledge separate from short summaries.

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/digipulse-engineering/gaai-framework/memory-retrieve
Any agent
npx skills add digipulse-engineering/GAAI-framework --skill memory-retrieve
Clone the repo
git clone --depth 1 https://github.com/digipulse-engineering/GAAI-framework

Made for: Claude Code, Codex.

Per session 38 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,509 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown 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 $0.00038 $0.01509
Opus 5 $0.00019 $0.00754
Sonnet 5 $0.00008 $0.00302
Haiku 4.5 $0.00004 $0.00151

Measured 2d ago against content hash 7b125ed23616, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

memory-retrieve 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 2d 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.

.gaai/core/skills/cross/memory-retrieve/SKILL.md · 145 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

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. 2d ago First seen · 145 lines · 38 tokens per session scan A 7b125ed23616

Subscribe to this mod's changes

memory-retrieve is a skill published in the GitHub repository digipulse-engineering/GAAI-framework (161 stars, last pushed 2d ago), with no licence file. It adds 38 tokens to every session and 1,509 once invoked, about $0.0002 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

chart

Use when the user asks to visualize data with charts, graphs, or plots using the chart tool (bar, line, scatter, pie, time series, etc.).

Kilo-Org/kilocode · 37 tokens

performance

CLI performance optimization - startup time, memory usage, token savings benchmarking.

rtk-ai/rtk · 13 tokens

build-teaql-app

Build or change a TeaQL application in Java, Rust, Go, Swift, Python, C#/.NET, or TypeScript, including Kotlin/JVM applications that consume Java-generated libraries. Mandatory order: first draft and save a complete KSML model, then verify the client and evaluate that saved model, repair it through repeated evaluation…

teaql/teaql-agent-kit · 112 tokens

writing-tests

Write unit tests, component tests, and integration tests for AiderDesk using Vitest and React Testing Library. Use when creating new tests, adding test coverage, configuring mocks, setting up test files, or debugging failing tests.

hotovo/aider-desk · 48 tokens

orchestrator-lanes

Claude Code dev-orchestrator only. File-based multi-lane PM playbook (score, DAG, run-controller, L0/L1/L2, ship). Use when this session IS that agent, or user says info / справка / lane-stack:orchestrator-lanes info. SKIP: Grok, Codex, Kimi, Qwen, AGY, Cursor writer CLIs and any default coding agent — do not load, do…

VKirill/claude-lane-stack · 104 tokens

source-command-methodology-advisor

Analyzes your codebase and asks 3 targeted questions to recommend the right AI-assisted development methodology stack.

FlorianBruniaux/claude-code-ultimate-guide · 27 tokens