memory-onboarding

A guided process for helping a new Basic Memory user design and build a personal knowledge system. It starts by asking what they want to track, then proposes a structure and explains how to use it.

In plain words
What is it for?
Use it to plan note structures, create schemas and instruction notes, teach Basic Memory workflows, and configure an AI assistant to load the system automatically.
Why use it?
It turns an unclear collection of personal information into an organised system with useful instructions. It also helps the user understand the system after it is built.

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/basicmachines-co/basic-memory/memory-onboarding
Any agent
npx skills add basicmachines-co/basic-memory --skill memory-onboarding
Clone the repo
git clone --depth 1 https://github.com/basicmachines-co/basic-memory

Made for: Claude Code, Codex.

Per session 148 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,069 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 $0.00148 $0.03069
Opus 5 $0.00074 $0.01535
Sonnet 5 $0.00030 $0.00614
Haiku 4.5 $0.00015 $0.00307

Measured yesterday against content hash 11115eff672d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

memory-onboarding 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.

skills/memory-onboarding/SKILL.md · 143 lines

The source is not reproduced here

Licensed AGPL-3.0

The repository is licensed AGPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.

Read it on GitHub

Files

What ships with it

5 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 · 143 lines · 148 tokens per session scan A 11115eff672d

Subscribe to this mod's changes

memory-onboarding is a skill published in the GitHub repository basicmachines-co/basic-memory (3,804 stars, last pushed yesterday), licensed AGPL-3.0. It adds 148 tokens to every session and 3,069 once invoked, about $0.0007 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

refine

End-of-session reflection. Reviews friction encountered during the session and proposes updates to docs/ to capture lessons learned.

windmill-labs/windmill · 25 tokens

learn

Close a Hardproof run during LEARN by capturing safe provenance-linked lessons or recording an explicit reason to skip them.

asimons81/hardproof · 25 tokens

write-copy

Extract all text content from a video — visible text via OCR and spoken narration via transcript. Returns clean organized copy ready to use verbatim. Use for marketing videos, app demos, or tutorials.

gowtham012/Claude-plugins · 42 tokens

remember

Review the current conversation and capture valuable knowledge — best practices, coding conventions, architecture decisions, workflows, and user feedback — into persistent memory (AGENTS.md) or reusable skills. Use when the user says: (1) remember this, (2) save what we learned, (3) update memory, (4) capture…

langchain-ai/deepagents · 71 tokens

mem0-tour

Browses all stored memories grouped by category with full content display. Use when reviewing all project memories, exploring stored knowledge, onboarding to a project, or getting an overview of captured decisions, conventions, and learnings.

mem0ai/mem0 · 47 tokens

mem0-remember

Stores a memory verbatim from user input with appropriate type classification and metadata. Use when the user says remember this, save this, store this, note that, or explicitly asks to record a decision, preference, convention, or learning.

mem0ai/mem0 · 52 tokens