ai-memory-retrieval

ai-memory-retrieval is a skill for Claude Code, Codex from akitaonrails/ai-memory. It costs 65 tokens per session (1,501 once invoked), scanned A, original, MIT.

A read-only lookup tool for an AI memory store containing project history, earlier decisions, rules, warnings, recent activity, and status information.

In plain words
What is it for?
Use it to search project memory, read full wiki pages, review recent updates, inspect stored session observations, or get a project briefing.
Why use it?
It helps recover relevant context without relying on the current conversation alone.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to search project memory, read full wiki pages, review recent updates, inspect stored session observations, or get a project briefing.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/akitaonrails/ai-memory/ai-memory-retrieval
About the project

ai-memory is a shared long-term memory system for coding agents that preserves project knowledge, unfinished work, failed approaches, and open questions across tools and machines. It is used by individual developers and teams to hand work between different coding agents and continue projects without repeating the context.

akitaonrails/ai-memory · 6,432 stars · on GitHub

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.

Any agent
npx skills add akitaonrails/ai-memory --skill ai-memory-retrieval
Clone the repo
git clone --depth 1 https://github.com/akitaonrails/ai-memory

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 ai-memory-retrieval

README.md
[![agentmods](https://agentmods.dev/badge/skills/akitaonrails/ai-memory/ai-memory-retrieval/github.svg)](https://agentmods.dev/skills/akitaonrails/ai-memory/ai-memory-retrieval)
Your own site
<a href="https://agentmods.dev/skills/akitaonrails/ai-memory/ai-memory-retrieval"><img src="https://agentmods.dev/badge/skills/akitaonrails/ai-memory/ai-memory-retrieval/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for ai-memory-retrieval

Your own site · 80×15
<a href="https://agentmods.dev/skills/akitaonrails/ai-memory/ai-memory-retrieval"><img src="https://agentmods.dev/badge/skills/akitaonrails/ai-memory/ai-memory-retrieval.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 65 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,501 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 5.1 $0.00065 $0.01501
Opus 5 $0.00032 $0.00750
Sonnet 5 $0.00013 $0.00300
Haiku 4.5 $0.00006 $0.00150

Measured 4d ago against content hash 838eed977750, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

ai-memory-retrieval 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.

crates/ai-memory-core/src/routing_skills/ai-memory-retrieval/SKILL.md · 90 lines

How it starts

The opening of the file, as written. The whole thing — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.

ai-memory retrieval

Use this skill for read-only ai-memory lookups, catch-up, and evaluating remembered project knowledge before you design, debug, or edit.

Tools in this cluster

  • memory_query searches the current project's wiki for prior decisions, gotchas, procedures, rules, and session notes.
  • memory_recent lists the most recently updated pages when the user wants a light activity check.
  • memory_read_page fetches a full page body after a search hit or direct path lookup.
  • memory_read_session_observations reads one session's raw hook observations (prompts, tool calls, stops) in capture order, paged and body-capped, when the user asks what actually happened in a session or wants to check a compiled page against its evidence.
  • memory_status reports whether ai-memory is healthy and how large the knowledge base is.
  • memory_briefing returns a structured read-only snapshot for agent consumption.
  • memory_explore returns a prose digest when the user asks for an open-ended catch-up.

Project scope

Choose scope from the MCP client's identity support:

  • Session-aware MCP clients that forward the real lifecycle-hook session id on every request should use automatic current-project routing. Omit workspace, project, and cwd for the current repository; pass explicit scope only when the user names a different project.
  • Static MCP clients (including clients with lifecycle hooks but no bridge connecting that hook session id to MCP requests) must pass workspace and project together on every project-scoped call, including requests about this project, here, or our work. Read the exact names from the nearest .ai-memory.toml when it declares both. If it does not, obtain the names from the operator or server configuration; never guess them from a directory name and never rely on the server's last active project.

This rule applies only to project-scoped calls. For cross-project retrieval, global=true must omit workspace, project, and scopes. For a standing preference written with scope: "global", omit workspace and project.

Read the full file on GitHub · 90 lines

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 Changed · +5 lines 838eed977750
  2. 12d ago First seen · 85 lines · 65 tokens per session scan A 31de3bbcc3ff

Subscribe to this mod's changes

ai-memory-retrieval is a skill published in the GitHub repository akitaonrails/ai-memory (6,432 stars, last pushed yesterday), licensed MIT. It adds 65 tokens to every session and 1,501 once invoked, about $0.0003 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.

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