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Basic Memory

Memory serverOfficial Basic Machines project

Created by Basic Machines

Published in basicmachines-co/basic-memory. Publisher page

4,552 GitHub stars

What it is

AI conversations that actually remember. Never re-explain your project to your AI again. Join our Discord: https://discord.gg/tyvKNccgqN
— the description by Basic Machines

AutoGineer overview, from the brain’s own files

Basic Memory is a memory system designed to give AI agents persistent, long-term recall. It operates as an MCP server that bridges the gap between human-readable Markdown files and AI agent context. By treating a directory of Markdown files as a knowledge graph, it allows agents to read, write, and search information across sessions. It supports both local-first operation for privacy and an optional cloud-hosted service for cross-device synchronization. The system includes advanced features like semantic vector search, hybrid full-text retrieval, and a schema system for validating knowledge structure, ensuring that agents can reliably store and retrieve project context, learnings, and documentation.

How it works

Memory model: Hybrid

AutoGineer overview, from the brain’s own files

Basic Memory functions as an MCP server that monitors and manages a collection of Markdown files on your disk. It uses a hybrid memory model that combines standard file-based storage with a database layer (SQLite or Postgres) to enable semantic search and vector indexing. When an agent interacts with the server, it uses specific tools to ingest, curate, or retrieve information from these files. The system automatically handles file synchronization and provides metadata-rich search results, allowing agents to maintain context across different tasks and projects without needing to re-learn information.

Folders
FolderRoleFiles
.claudeagent-config15
.codexagent-config1
.githubagent-config20
docsdocs41
scriptsscripts16
skillsagent-instructions33
srcsource-code529
teststests595
.agentsfolder58
.claude-pluginfolder1
benchmarksfolder155
integrationsfolder175
pluginsfolder72
test-intfolder179

The agent reads

The agent writes

Requirements

Runtimes: Python >=3.12

Databases: Milvus, PostgreSQL, Redis, SQLite

API keys (by name): COHERE_API_KEY, OPENAI_API_KEY

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Google Antigravity, Kiro, OpenCode, Amp, Roo Code, Cline, JetBrains Junie, Devin (ex-Windsurf)

Set it up

  1. This brain runs code automatically: 4 hooks (claude-code, codex), 1 script. Review plugins/claude-code/hooks/hooks.json, plugins/codex/hooks/hooks.json, src/basic_memory/cli/commands/install.py before opening the folder in Claude Code. No step below turns a hook on for you.

    • plugins/claude-code/hooks/hooks.json: uv run --quiet --script "${CLAUDE_PLUGIN_ROOT}/hooks/session_start.py"
    • plugins/claude-code/hooks/hooks.json: uv run --quiet --script "${CLAUDE_PLUGIN_ROOT}/hooks/pre_compact.py"
    • plugins/codex/hooks/hooks.json: uv run --quiet --script "${PLUGIN_ROOT}/hooks/session_start.py"
    • plugins/codex/hooks/hooks.json: uv run --quiet --script "${PLUGIN_ROOT}/hooks/pre_compact.py"
    • src/basic_memory/cli/commands/install.py: python src/basic_memory/cli/commands/install.py
  2. Not scanned by AutoGineerIts dependencies are installed by pip or uv when you run it and were not scanned by AutoGineer (43 declared). https://pypi.org/project/basic-memory/

  3. Created by Basic Machines. Published in basicmachines-co/basic-memory. Licence: GNU Affero General Public License v3.0 only.

Usage

AutoGineer overview, from the brain’s own files

  • Connect the server to an MCP-compatible AI client like Claude Desktop, Cursor, or Codex.
  • Use natural language prompts to save project decisions, research findings, or daily logs directly into your memory vault.
  • Query the agent to retrieve specific information from past conversations or project documentation.
  • Edit notes manually in any Markdown editor while the agent simultaneously updates or references the same files.
“Create a note about our project architecture decisions.”
The agent creates a new Markdown file in the vault containing the documented architecture, which is then indexed for future retrieval.
“Find information about JWT auth in my notes.”
The agent performs a semantic search across the vault and returns relevant snippets or links to notes discussing JWT implementation.
“What have I been working on this week?”
The agent analyzes the recent file activity and notes to provide a summary of your progress and active tasks.

Documentation by Basic Machines

<!-- mcp-name: io.github.basicmachines-co/basic-memory -->

Image: MCP Toplist

Image: License: AGPL v3 Image: PyPI version Image: Python 3.12+ Image: Tests Image: Ruff Image: untitled Image: untitled Image: Ask DeepWiki

Skip the install — try Basic Memory in the cloud

Claude, Codex, or Cursor connected in 30 seconds. No Python, no JSON, no terminal. $15.00/mo locked in for life (12.50/mo yearly pricing). 7-day free trial — cancel any time before day 7 if it's not for you. Beta pricing — sign up now and your rate never goes up. OSS users: code BMFOSS takes another 20% off for 3 months.

Start free trial →

Basic Memory Teams is now available!

Give your team a single, shared cloud workspace. Knowledge isn't confined to one person — anything a teammate writes is immediately available to everyone else and to their AI assistants. Edit a note together in real time, hand work off between humans and agents, and build one connected knowledge base instead of scattered copies. Same pricing - start with one user and add more as needed.

Basic Memory

Your AI never forgets again.

Pick up right where you left off — in Claude, Codex, Cursor, ChatGPT, or anything that speaks MCP. Your knowledge lives as Markdown files that both you and your AI can read, write, and search.

  • Local-first. Plain text on your disk. Forever.

  • Two-way. AI and humans write to the same files; sync keeps them in step.

  • A real knowledge graph. Observations and wikilinks compound into context.

  • Semantic search. Find notes by meaning, not just keywords, with optional cross-encoder reranking for higher-quality vector and hybrid results.

  • MCP-native. Works with every major AI client and IDE.

  • Progressive tool discovery. Every tool is tagged with behavior hints (read-only, destructive, idempotent) so agents pick the right tool on demand — no wasted context trying things to see what they do.

  • Cloud, optional. Sync across devices when you want — never required.

Get started

Pick the path that fits you. Both run the same product on the same Markdown.

<table> <tr> <th width="50%">☁️ &nbsp; Cloud</th> <th width="50%">💻 &nbsp; Local install</th> </tr> <tr> <td valign="top">

30 seconds. Sign up, connect your AI client, done.

  • Works in any browser

  • Mobile, web, desktop

  • Cross-device sync built in

  • We handle hosting, backups, snapshots

$15.00/mo locked for life · 7-day free trial · cancel any time

Start free trial →

</td> <td valign="top">

2 minutes. Install, configure your AI client, run.

  • Free forever (AGPL-3.0)

  • All data on your disk

  • Air-gapped friendly

  • Requires Python via uv

uv tool install basic-memory --prerelease=allow

--prerelease=allow is required: Basic Memory 0.23 depends on a FastMCP 4 pre-release, and uv only accepts pre-releases of transitive dependencies when told to — without the flag it silently installs an older release. The same flag goes on every uvx / uv tool upgrade command below.

For Postgres deployments that store semantic vectors in Milvus, install the first-party optional extra instead:

uv tool install "basic-memory[milvus]" --prerelease=allow

Configure your client ↓

</td> </tr> </table>

What people are saying

Basic Memory changed my whole relationship with LLMs. I switched from GPT and Gemini to exclusively Claude and Claude Code because of this integration and am completely revamping all our company's processes around a Basic Memory workflow.

— Alex, TrainerDay

Basic Memory is the missing 'wow' factor in AI chatbots. Now I can't imagine Claude or Claude Code without it.

— Caleb, Caleb Picker Consulting

I don't code without Basic Memory anymore. It's such a time saver to be able to refer to projects I don't currently have active and keep a running log of all my learnings and ProTips.

— @groksrc, Developer

More on basicmemory.com.

Basic Memory Cloud

The hosted version of Basic Memory. Same product, same Markdown files, same MCP tools — we just host the database, run the sync, and put it on your phone.

What you get

  • Every device, same brain. Your knowledge graph on web, mobile, and desktop. No copy-paste between machines.

  • Connect any MCP client. Claude Desktop, Claude Code, Codex, Cursor, ChatGPT (Custom GPTs), VS Code — one-click connect from the web app.

  • Bidirectional sync to local. Edit on your phone, see it in Obsidian on your laptop. rclone-powered with conflict resolution.

  • Snapshots and backups. Point-in-time restore. Browse history. Never lose a note.

  • No lock-in. Your notes are plain Markdown. Export to local Markdown any time — same files, same format, same wikilinks. Cancel anytime, your data stays yours.

Built on WorkOS AuthKit, Neon Postgres, and Tigris S3.

Pricing

$15.00/mo, locked in for the life of your subscription (regular price $19). Sign up during beta and the rate never goes up — as long as you stay subscribed, you keep the price. One plan, no tiers, no surprise upgrades. Unlimited notes, unlimited projects, every feature.

  • 7-day free trial. Cancel any time before day 7 if it's not for you.

  • Cancel anytime after that too — export your notes whenever you want.

  • OSS users: code BMFOSS for another 20% off for 3 months (~$11.40/mo).

Start your 7-day free trial →

Cloud vs. local

CloudLocal
Setup time30 seconds2 minutes (requires Python)
Cost$15.00/mo, locked for life (7-day trial)Free
StorageWe host (Tigris S3)Your disk
Cross-device syncBuilt inManual (Git, Syncthing, etc.)
Mobile accessYes (web + app)No
Air-gappedNoYes
Your data stays yoursYes — export anytimeYes — already there
Source codeAGPL-3.0AGPL-3.0
Snapshots & backupsBuilt inRoll your own

Both paths use the same OSS engine and the same Markdown files. There's no lock-in either way — flip between them when your needs change.

Works with the tools you already use

ClientTransportNotes
Cloud web apphttpsSign in at basicmemory.com — no install
Claude Desktopstdio/httpsmacOS / Windows / Linux
Claude Codestdio/httpsclaude mcp add
Codexstdio/httpsOpenAI's coding agent
Cursorstdio/https.cursor/mcp.json
VS Codestdio/httpsNative MCP support
ChatGPThttpsCustom GPT actions (search / fetch)
Obsidian—Reads/writes the same Markdown directly
Anything MCPstdio/httpsIf it speaks MCP, it works

Official agent packages

This repository is also the canonical home for Basic Memory's host-native agent packages. The core Python package, Claude Code plugin, shared skills, Hermes plugin, and OpenClaw plugin all ship from the same source tree.

Maintainers can verify the whole consolidated surface from the repo root:

just package-check

Package-local justfiles are also available when working inside one host:

just package-check-claude-code
just package-check-skills
just package-check-hermes
just package-check-openclaw
Claude Code plugin

The Claude Code plugin is the bridge between Claude's working memory and Basic Memory — session-start briefings, pre-compaction checkpoints, an opt-in capture output style, and /basic-memory:bm-setup · :remember · :share · :status.

Connect the Basic Memory MCP server first — see Connect your AI client. The plugin's hooks and skills call it, so it's a hard prerequisite. Then install the plugin:

bm install claude-code

That registers the marketplace and installs the plugin through Claude Code. Add --scope project to declare both in the repository's settings for a team, or --dry-run to see the underlying claude plugin commands without running them.

Source: plugins/claude-code.

Shared skills

Framework-agnostic SKILL.md files live in skills/. If your Skills CLI supports repository subdirectory sources:

npx skills add basicmachines-co/basic-memory/skills -g

For Claude and ChatGPT, upload basic-memory.zip or basic-memory-chatgpt.zip from the skills-latest release; see skills/README.md.

If your installed Skills CLI cannot load that source, update the CLI or copy the memory-* directories from skills/ into your agent's skills directory.

Hermes

Hermes keeps its native plugin shape under integrations/hermes:

hermes plugins install basicmachines-co/basic-memory/integrations/hermes

Hermes does not install a plugin's Python dependencies, so also add the mcp package to the Hermes venv — see the plugin README for that step and the supported Hermes releases.

OpenClaw

OpenClaw stays package-native and publishes from integrations/openclaw:

openclaw plugins install @basicmemory/openclaw-basic-memory

Pick up where you left off

https://github.com/user-attachments/assets/a55d8238-8dd0-454a-be4c-8860dbbd0ddc

Connect your AI client

If you went the Cloud route, the web app walks you through client connect. The snippets below are for local installs.

Claude Desktop

Edit ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "basic-memory": {
      "command": "uvx",
      "args": ["--prerelease=allow", "basic-memory", "mcp"]
    }
  }
}

Restart Claude Desktop. Notes live in ~/basic-memory by default.

<details> <summary><b>Claude Code, Codex CLI, Cursor, VS Code, ChatGPT, Obsidian</b></summary>

Claude Code
claude mcp add basic-memory -- uvx --prerelease=allow basic-memory mcp

For the full memory bridge — session briefings, pre-compaction checkpoints, and the /basic-memory:* commands — also install the Claude Code plugin on top of this.

Codex CLI

Add to ~/.codex/config.toml:

[mcp_servers.basic-memory]
command = "uvx"
args = ["--prerelease=allow", "basic-memory", "mcp"]

Codex can keep its default MCP approval behavior, or you can pre-approve eligible Basic Memory tools by adding this server-scoped setting to the same table:

[mcp_servers.basic-memory]
command = "uvx"
args = ["--prerelease=allow", "basic-memory", "mcp"]
default_tools_approval_mode = "approve"

This does not disable Codex approvals globally or expand which Basic Memory projects the server can access. Codex still requires approval for tools that advertise a destructive annotation, including Basic Memory's writes, edits, and deletes. If you installed the Basic Memory Codex plugin, use its plugin-scoped configuration instead.

Cursor

Add to .cursor/mcp.json (project) or ~/.cursor/mcp.json (global):

{
  "mcpServers": {
    "basic-memory": {
      "command": "uvx",
      "args": ["--prerelease=allow", "basic-memory", "mcp"]
    }
  }
}
VS Code

Add to your User Settings (JSON):

{
  "mcp": {
    "servers": {
      "basic-memory": {
        "command": "uvx",
        "args": ["--prerelease=allow", "basic-memory", "mcp"]
      }
    }
  }
}
ChatGPT

Basic Memory exposes OpenAI-compatible search and fetch tools for Custom GPT actions. See the ChatGPT integration guide.

Obsidian

No setup. Point Obsidian at ~/basic-memory (or your project folder) and the same wikilinks, frontmatter, and Markdown your AI writes appear in your graph view. Edit either side — sync handles the rest.

</details>

Try a prompt:

"Create a note about our project architecture decisions."
"Find information about JWT auth in my notes."
"What have I been working on this week?"

What's New

  • Automatic updates. Basic Memory keeps itself up to date for uv tool and Homebrew installs; bm update triggers a manual check.

  • Semantic vector search. Find notes by meaning, not just keywords. Hybrid full-text + vector ranking with FastEmbed embeddings, on SQLite or Postgres.

  • Optional search reranking. Rescore the strongest vector and hybrid candidates with a local FastEmbed cross-encoder or a LiteLLM-backed provider.

  • Schema system. Infer, validate, and diff the structure of your knowledge base with bm_schema_infer(), bm_schema_validate(), and bm_schema_diff().

  • Per-project cloud routing. Route individual projects through the cloud while others stay local, via API key (bm project set-cloud).

  • Explicit note changes. bm_edit updates existing notes; bm_write creates notes and guards against accidental overwrites.

  • Richer search results. Matched chunk text is included so the LLM gets context, not just hits.

  • FastMCP 3.0 + tool annotations. Every tool ships with MCP behavior hints (readOnlyHint, destructiveHint, idempotentHint, openWorldHint) so agents can discover capabilities progressively at runtime instead of guessing or burning tokens.

  • CLI overhaul. --json output for scripting, workspace-aware commands, and an htop-inspired project dashboard.

Full CHANGELOG for v0.18 → v0.20.

Optional cross-encoder reranking

Reranking adds a second relevance pass after vector or hybrid retrieval. It is disabled by default because it adds inference latency and, for the local provider, a first-run model download. Text, title, and permalink searches keep their existing ranking.

Enable the default local FastEmbed reranker:

export BASIC_MEMORY_RERANKER_ENABLED=true

The default model is jinaai/jina-reranker-v1-tiny-en. To use a hosted reranker through LiteLLM instead, first install the optional LiteLLM SDK, then configure it:

export BASIC_MEMORY_RERANKER_ENABLED=true
export BASIC_MEMORY_RERANKER_PROVIDER=litellm
export BASIC_MEMORY_RERANKER_MODEL=cohere/rerank-v3.5
export COHERE_API_KEY=...

The feature fails fast on invalid configuration and does not silently fall back to retrieval order when an enabled provider fails. See the semantic search guide for provider setup, all settings, tuning, pagination, and failure behavior.

Why Basic Memory

Most LLM conversations are ephemeral. You ask a question, get an answer, then everything is forgotten. Workarounds have limits:

  • Chat history captures conversations but isn't structured knowledge.

  • RAG lets the LLM query your documents but not write back to them.

  • Vector DBs need complex infra and usually live in someone else's cloud.

  • Knowledge graphs need specialized tooling to maintain.

Basic Memory takes a simpler path: structured Markdown files that humans and LLMs both read and write.

  • All knowledge stays in plain files you control.

  • Both sides read and write to the same files.

  • Familiar Markdown with semantic patterns — no new format to learn.

  • A traversable graph the LLM can follow link by link.

  • Works with the editors you already use (Obsidian, VS Code, anything).

  • Just files plus a local SQLite index. No servers required.

How it works

You're chatting normally about coffee:

I've been experimenting with brewing methods. Pour over gives more clarity than French press, water at 205°F seems best, and freshly ground beans make a huge difference.

Ask the LLM to capture it:

"Make a note on coffee brewing methods."

A Markdown file appears in your project directory in real time:

---
title: Coffee Brewing Methods
permalink: coffee-brewing-methods
tags: [coffee, brewing]
---

# Coffee Brewing Methods

## Observations
- [method] Pour over highlights subtle flavors over body
- [technique] Water at 205°F (96°C) extracts optimal compounds
- [principle] Freshly ground beans preserve aromatics

## Relations
- relates_to [[Coffee Bean Origins]]
- requires [[Proper Grinding Technique]]
- affects [[Flavor Extraction]]

Next session, the LLM picks up the thread. It follows the relations to surface what you already know about Ethiopian beans and burr grinders, and builds on it instead of starting over. You see the same files in Obsidian or your editor. Edit them by hand — the AI sees your changes too.

Real two-way flow: humans edit Markdown, LLMs read/write through MCP, sync keeps everything consistent, and the source of truth is always your files.

The Markdown format

Each file is an Entity. Entities have Observations (facts about them) and Relations (links to other entities). That's the whole grammar.

Frontmatter
---
title: <Entity title>
type: note
permalink: <uri-slug>
tags: [optional, list]
---
Observations

Facts about the entity. Categories in [brackets], tags with #, optional context in parens.

- [method] Pour over highlights subtle flavors
- [tip] Grind medium-fine for V60 #brewing
- [fact] Lighter roasts contain more caffeine than dark
- [resource] James Hoffmann's V60 technique on YouTube
- [question] How does temperature affect compound extraction?
Relations

Wiki-style links that form the graph. Single-token relation types, or quote multi-word ones.

- pairs_well_with [[Chocolate Desserts]]
- grown_in [[Ethiopia]]
- requires [[Burr Grinder]]
- "pairs well with" [[Dark Chocolate]]

Bare - [[Target]] and prose - Worth checking out [[Target]] index as links_to. Full reference in the docs.

MCP tools

Basic Memory exposes these tools to any MCP client. Every tool is annotated with MCP behavior hints (read-only, destructive, idempotent, open-world) so agents can pick the right one without trial-and-error:

  • Content: bm_write, bm_read, bm_edit, bm_move, bm_delete

  • Search & discovery: bm_search, bm_list, bm_find

  • Knowledge graph: bm_context

  • Projects: bm_project_list, bm_project_create, bm_recent; bm_project_delete is separate and requires server opt-in.

  • Schema: bm_schema_validate, bm_schema_infer, bm_schema_diff

  • Manual: bm_man

  • Cloud connector adapters: search and fetch are registered by Cloud only. Local diagnostics use bm doctor.

Most tools default to text; bm_context defaults to JSON. Pass output_format="json" for structured responses. Project-scoped tools accept a name, workspace/project, or external UUID through project. Use bm_man(page="bm-search(3)") for the installed contract, or see the tool guide. CLI commands retain their shell names.

CLI essentials

# Projects
basic-memory project list
basic-memory project add research ~/research
basic-memory project set-cloud research   # route through cloud
basic-memory project set-local research   # revert

# Config
basic-memory config list                        # all settings, effective values, env overrides
basic-memory config set cli_output_style plain  # validated through the config model
basic-memory config unset cli_output_style      # revert to default

# Health & maintenance
basic-memory status
basic-memory doctor              # report project problems and the commands that fix them
basic-memory tool edit ...  # CLI access to MCP tools
basic-memory update              # check for and install updates

# Imports
basic-memory import claude conversations
basic-memory import chatgpt
basic-memory import memory-json

Routing flags (--local / --cloud) force a target when you're in mixed mode. Full CLI reference in the docs.

Auto-updates

CLI installs check for updates every 24 hours by default and apply them silently (so the MCP server keeps responding).

  • Supported install sources: uv tool, Homebrew

  • Skipped for uvx (ephemeral runtime managed by uv)

  • Manual: bm update (check + apply) or bm update --check (check only)

Disable in ~/.basic-memory/config.json:

{ "auto_update": false }

Telemetry

Minimal, anonymous events to understand the CLI-to-cloud conversion funnel.

What we collect: cloud promo impressions, cloud login attempts and outcomes, promo opt-out events.

What we don't: file contents, note titles, knowledge base data, PII, IP addresses, per-command or per-tool tracking.

Events go to our Umami Cloud instance (open-source, privacy-focused) on a background thread — never blocks the CLI.

Opt out:

export BASIC_MEMORY_NO_PROMOS=1

This disables promos and all telemetry.

Logging

Basic Memory uses Loguru. Defaults vary by entry point:

Entry pointDefaultWhy
CLI commandsFile onlyDoesn't interfere with command output
MCP serverFile onlyStdout would corrupt JSON-RPC
API serverFile (local) or stdout (cloud)Docker/cloud uses stdout

Log file: ~/.basic-memory/basic-memory.log (10MB rotation, 10 days retention).

Environment variables
VariableDefaultDescription
BASIC_MEMORY_LOG_LEVELINFODEBUG / INFO / WARNING / ERROR
BASIC_MEMORY_CLOUD_MODEfalseAPI logs to stdout with structured context
BASIC_MEMORY_FORCE_LOCALfalseForce local API routing
BASIC_MEMORY_FORCE_CLOUDfalseForce cloud API routing
BASIC_MEMORY_EXPLICIT_ROUTINGfalseMark route selection as explicit
BASIC_MEMORY_ENVdevSet to test for test mode (stderr only)
BASIC_MEMORY_NO_PROMOSfalseDisable cloud promos and telemetry
BASIC_MEMORY_IMPORT_UPLOAD_MAX_BYTES104857600Max uploaded import size
BASIC_MEMORY_LOG_LEVEL=DEBUG basic-memory reindex
tail -f ~/.basic-memory/basic-memory.log

Development

Basic Memory supports SQLite (default, fast, no Docker) and Postgres (via testcontainers — Docker required).

just install          # Install with dev dependencies
just test-sqlite      # All tests, SQLite
just test-postgres    # All tests, Postgres (testcontainers)
just test             # Both backends
just fast-check       # fix/format/typecheck + impacted tests
just doctor           # File <-> DB consistency check (temp config)
just package-check    # Claude Code, skills, Hermes, OpenClaw package checks
just lint
just typecheck        # Pyright (primary)
just typecheck-ty     # ty (supplemental)
just format
just check            # All quality checks
just migration "msg"  # New Alembic migration

Tests use pytest markers: windows, benchmark, smoke. See justfile for the full list.

Contributions welcome — see CONTRIBUTING.md.

License

AGPL-3.0.

Built with ♥️ by Basic Machines

docs/NOTE-FORMAT.md

Note Format Reference

Every document in Basic Memory is a plain Markdown file. Files are the source of truth — changes to files automatically update the knowledge graph in the database. You maintain complete ownership, files work with git, and knowledge persists independently of any AI conversation.

Document Structure

A note has three parts: YAML frontmatter, content (observations), and relations.

---
title: Coffee Brewing Methods
type: note
tags: [coffee, brewing]
permalink: coffee-brewing-methods
---

# Coffee Brewing Methods

## Observations
- [method] Pour over provides more flavor clarity than French press
- [technique] Water temperature at 205°F extracts optimal compounds #brewing
- [preference] Ethiopian beans work well with lighter roasts (personal experience)

## Relations
- relates_to [[Coffee Bean Origins]]
- requires [[Proper Grinding Technique]]
- contrasts_with [[Tea Brewing Methods]]

The ## Observations and ## Relations headings are conventional but not required — the parser detects observations and relations by their syntax patterns anywhere in the document.

Frontmatter

YAML metadata between --- fences at the top of the file.

FieldRequiredDefaultDescription
titleNofilename stemUsed for linking and references. Auto-set from filename if missing.
typeNonoteEntity type. Used for schema resolution and filtering.
tagsNo[]List or comma-separated string. Used for organization and search.
permalinkNogenerated from titleStable identifier. Persists even if the file moves.
createdNofile ctimeCanonical semantic creation timestamp. Accepts ISO 8601 dates or datetimes.
modifiedNofile mtimeCanonical semantic modification timestamp. Accepts ISO 8601 dates or datetimes.
schemaNononeSchema attachment — dict (inline), string (reference), or omitted (implicit).

Custom fields are allowed. Any key not in the standard set is stored as entity_metadata and indexed for search and filtering.

---
title: Paul Graham
type: Person
tags: [startups, essays, lisp]
permalink: paul-graham
status: active
source: wikipedia
---

Here status and source are custom fields stored in entity_metadata.

Frontmatter Value Handling

YAML automatically converts some values to native types. Basic Memory normalizes them:

  • Date strings (2025-10-24) → kept as ISO format strings

  • Numbers (1.0) → converted to strings

  • Booleans (true) → converted to strings ("True")

  • Lists and dicts → preserved, items normalized recursively

This prevents errors when downstream code expects string values.

Canonical Note Timestamps

created and modified describe the note, not the current file object. Basic Memory parses these canonical fields once when it accepts or indexes Markdown and carries the resulting typed values through entity, search, and directory projections.

  • Date-only values use midnight in the machine's local timezone.

  • Datetimes without an offset use the machine's local timezone.

  • Explicit UTC or numeric offsets remain unchanged.

  • A missing or null field falls back independently to the file's ctime or mtime. When file stats are unavailable, both missing values use one timestamp from the current operation.

  • An invalid canonical value is an indexing error for that field; Basic Memory does not silently replace it with a file timestamp.

Filesystem mtime, checksum, size, and path remain physical synchronization bookkeeping. A move, materialization, or incidental bookkeeping update does not change a note's semantic timestamps. Passive indexing does not add or rewrite created or modified; notes without them remain compatible through the filesystem fallback. Timestamp aliases are not canonical fields.

Observations

An observation is a categorized fact about the entity. Written as a Markdown list item.

Syntax:

- [category] content text #tag1 #tag2 (context)
PartRequiredDescription
[category]YesClassification in square brackets. Any text except []() chars.
contentYesThe fact or statement.
#tagsNoInline tags. Space-separated, each starting with #.
(context)NoParenthesized text at end of line. Supporting details or source.
Examples
- [tech] Uses SQLite for storage #database
- [design] Follows local-first architecture #architecture
- [decision] Selected bcrypt for passwords #security (based on OWASP audit)
- [name] Paul Graham
- [expertise] Startups
- [expertise] Lisp
- [expertise] Essay writing

Array-like fields use repeated categories — multiple [expertise] observations above.

What Is Not an Observation

The parser excludes these list item patterns:

PatternExampleReason
Checkboxes- [ ] Todo item, - [x] Done, - [-] CancelledTask list syntax
Markdown links- [text](url)URL link syntax
Bare wiki links- [[Target]]Treated as a links_to relation instead

A list item with #tags but no [category] is still parsed — the tags are extracted and the category defaults to Note.

Relations

Relations connect documents to form the knowledge graph. There are two kinds.

Explicit Relations

Written as list items with a relation type and a [[wiki link]] target. Unquoted relation types are single tokens. Quote relation types that contain spaces.

Syntax:

- relation_type [[Target Entity]] (context)
- "multi word relation type" [[Target Entity]] (context)
- 'multi word relation type' [[Target Entity]] (context)
PartRequiredDescription
relation_typeYesSingle unquoted token before [[, or quoted text for multi-word labels.
[[Target]]YesWiki link to the target entity. Matched by title or permalink.
(context)NoParenthesized text after ]]. Supporting details.
Examples

Explicit relations:

- implements [[Search Design]]
- depends_on [[Database Schema]]
- works_at [[Y Combinator]] (co-founder)
- "based on" [[Customer Interview]]
- 'in response to' [[Incident Review]]

When the text before [[ is ordinary prose rather than a relation type, add #bm:links_to to force the reference to use the implicit links_to relation:

- Mother [[Alice]] #bm:links_to

The directive is parser metadata and is not included in the observation or relation context. It is especially useful when a single-token prose prefix would otherwise be interpreted as an explicit relation type.

Bare wiki links and prose list items create implicit links_to relations:

- [[Some Entity]]
- some other thing [[Some Entity]]

Both examples above create links_to [[Some Entity]]. Use quotes when the words before [[ are meant to be a multi-word relation type.

Common relation types:

  • implements, depends_on, relates_to, inspired_by

  • extends, part_of, contains, pairs_with

  • works_at, authored, collaborated_with

Any single-token text or quoted text works as a relation type. These are conventions, not a fixed set.

Inline References

Wiki links appearing in regular prose create implicit links_to relations. This includes list items that do not match the explicit relation grammar above.

This builds on [[Core Design]] and uses [[Utility Functions]].
- We should revisit [[Search Design]] after the API changes.

This creates three relations: links_to [[Core Design]], links_to [[Utility Functions]], and links_to [[Search Design]].

Forward References

Relations can link to entities that don't exist yet. Basic Memory resolves them when the target is created.

Permalinks and memory:// URLs

Every document has a unique permalink — a stable identifier derived from its title. You can set one explicitly in frontmatter, or let the system generate it.

permalink: auth-approaches-2024

Permalinks form the basis of memory:// URLs:

memory://auth-approaches-2024        # By permalink
memory://Authentication Approaches   # By title (auto-resolves)
memory://project/auth-approaches     # By path

Pattern matching is supported:

memory://auth*                       # Starts with "auth"
memory://*/approaches                # Ends with "approaches"
memory://project/*/requirements      # Nested wildcard

Schemas

Schemas declare the expected structure of a note — which observation categories and relation types a well-formed note should have. They use Picoschema, a compact notation from Google's Dotprompt that fits naturally in YAML frontmatter.

Picoschema Syntax
schema:
  name: string, full name              # required field with description
  email?: string, contact email        # ? = optional
  role?: string, job title
  works_at?: Organization, employer    # capitalized type = entity reference
  tags?(array): string, categories     # array of type
  status?(enum): [active, inactive]    # enum with allowed values
  metadata?(object):                   # nested object
    updated_at?: string
    source?: string
NotationMeaningExample
field: typeRequired fieldname: string
field?: typeOptional fieldrole?: string
field(array): typeArray of valuesexpertise(array): string
field?(enum): [vals]Enum with allowed valuesstatus?(enum): [active, inactive]
field?(object):Nested object with sub-fieldsmetadata?(object):
, descriptionDescription after commaname: string, full name
EntityNameCapitalized type = entity referenceworks_at?: Organization

Scalar types: string, integer, number, boolean, any

Any type not in that set whose first letter is uppercase is treated as an entity reference (a relation target).

Schema-to-Note Mapping

Schemas validate against existing observation/relation syntax. Note authors don't learn new syntax.

Schema DeclarationMaps ToExample in Note
field: stringObservation [field] value- [name] Paul Graham
field?(array): stringMultiple [field] observations- [expertise] Lisp (repeated)
field?: EntityTypeRelation field [[Target]]- works_at [[Y Combinator]]
field?(array): EntityTypeMultiple field relations- authored [[Book]] (repeated)
tagsFrontmatter tags arraytags: [startups, essays]
field?(enum): [vals]Observation [field] value where value is in the set- [status] active

Observations and relations not covered by the schema are valid — schemas describe a subset, not a straitjacket.

Schema Attachment

Three ways to attach a schema to a note, resolved in priority order:

1. Inline schema — schema is a dict in frontmatter:

---
title: Team Standup 2024-01-15
type: meeting
schema:
  attendees(array): string, who was there
  decisions(array): string, what was decided
  action_items(array): string, follow-ups
  blockers?(array): string, anything stuck
---

Good for one-off structured notes or prototyping a schema before extracting it.

2. Explicit reference — schema is a string naming a schema note:

---
title: Basic Memory
schema: SoftwareProject
---

or by permalink:

---
title: LLM Memory Patterns
schema: schema/research-project
---

Use when the note's type differs from the schema it should validate against, or when multiple schema variants exist.

3. Implicit by type — no schema field, resolved by matching type:

---
title: Paul Graham
type: Person
---

The system looks up a schema note where entity: Person. If found, it applies. If not, no validation occurs.

4. No schema — perfectly fine. Most notes don't need one.

Schema Notes

A schema is itself a Basic Memory note with type: schema. It lives anywhere (though schema/ is the conventional directory).

# schema/Person.md
---
title: Person
type: schema
entity: Person
version: 1
schema:
  name: string, full name
  role?: string, job title or position
  works_at?: Organization, employer
  expertise?(array): string, areas of knowledge
  email?: string, contact email
settings:
  validation: warn
---

# Person

A human individual in the knowledge graph.
FieldRequiredDescription
typeYesMust be schema
entityYesThe entity type this schema describes (e.g., Person)
versionNoSchema version number (default: 1)
schemaYesPicoschema dict defining the fields
settings.validationNoValidation mode (default: warn)

Schema notes are regular notes — they show up in search, can have observations and relations, and participate in the knowledge graph.

Validation Modes
ModeBehavior
warnWarnings in output, doesn't block (default)
strictErrors that block sync, for CI/CD enforcement

strict is the canonical enforcing mode. error is accepted as a compatibility alias and is normalized to strict. Any other value is rejected when the schema definition is parsed.

Validation Output
$ bm schema validate people/ada-lovelace.md

⚠ Person schema validation:
  - Missing required field: name (expected [name] observation)
  - Missing optional field: role
  - Missing optional field: works_at (no relation found)

ℹ Unmatched observations: [fact] ×2, [born] ×1
ℹ Unmatched relations: collaborated_with

"Unmatched" items are informational — observations and relations the schema doesn't cover.

Schema Inference

Generate schemas from existing notes by analyzing observation and relation frequency:

$ bm schema infer Person

Analyzing 30 notes with type: Person...

Observations found:
  [name]        30/30  100%  → name: string
  [role]        27/30   90%  → role?: string
  [expertise]   18/30   60%  → expertise?(array): string
  [email]        8/30   27%  → email?: string

Relations found:
  works_at      22/30   73%  → works_at?: Organization

Suggested schema:
  name: string, full name
  role?: string, job title
  expertise?(array): string, areas of knowledge
  email?: string, contact email
  works_at?: Organization, employer

Save to schema/Person.md? [y/n]

Frequency thresholds:

  • 100% present → required field

  • 25%+ present → optional field

  • Below 25% → excluded from suggestion

Schema Drift Detection

Track how usage patterns shift over time:

$ bm schema diff Person

Schema drift detected:

+ expertise: now in 81% of notes (was 12%)
- department: dropped to 3% of notes
~ works_at: cardinality changed (one → many)

Update schema? [y/n/review]

Complete Examples

Simple Note (No Schema)
---
title: Project Ideas
type: note
tags: [ideas, brainstorm]
---

# Project Ideas

## Observations
- [idea] Build a CLI tool for markdown linting #tooling
- [idea] Create a recipe knowledge base #cooking
- [priority] Focus on developer tools first (Q1 goal)

## Relations
- inspired_by [[Developer Workflow Research]]
- part_of [[Q1 Planning]]
Schema-Validated Note

Schema at schema/Person.md:

---
title: Person
type: schema
entity: Person
version: 1
schema:
  name: string, full name
  role?: string, job title or position
  works_at?: Organization, employer
  expertise?(array): string, areas of knowledge
  email?: string, contact email
settings:
  validation: warn
---

# Person

A human individual in the knowledge graph.

Note at people/paul-graham.md:

---
title: Paul Graham
type: Person
tags: [startups, essays, lisp]
---

# Paul Graham

## Observations
- [name] Paul Graham
- [role] Essayist and investor
- [expertise] Startups
- [expertise] Lisp
- [expertise] Essay writing
- [fact] Created Viaweb, the first web app

## Relations
- works_at [[Y Combinator]]
- authored [[Hackers and Painters]]

The [fact] observation and authored relation are not in the schema — they're valid, just unmatched. The schema only checks that [name] exists (required) and looks for optional fields like [role], [expertise], and works_at.

Inline Schema Note
---
title: Team Standup 2024-01-15
type: meeting
schema:
  attendees(array): string, who was there
  decisions(array): string, what was decided
  action_items(array): string, follow-ups
  blockers?(array): string, anything stuck
---

# Team Standup 2024-01-15

## Observations
- [attendees] Paul
- [attendees] Sarah
- [decisions] Ship v2 by Friday
- [action_items] Paul to review PR #42
- [blockers] Waiting on API credentials
512 files · 461 not served here

Advantages

  • Local-first architecture ensures data remains on your disk, providing air-gapped compatibility and full ownership. evidence: README.md
  • Bidirectional synchronization allows both humans and AI agents to edit the same files, keeping the knowledge base consistent. evidence: README.md
  • Progressive tool discovery via MCP behavior hints allows agents to select the most appropriate tool for a task without wasting context. evidence: README.md

Limitations

  • Local installation requires Python 3.12+ and familiarity with command-line tools. evidence: README.md
  • Cross-device synchronization for local-only setups requires manual configuration of tools like Git or Syncthing. evidence: README.md
  • Advanced features like cross-encoder reranking may introduce inference latency and require additional model downloads. evidence: README.md

Security

Risk level: Medium risk

This brain runs

Agent instructions that run or fetch something (322)

  • .agents/skills/adversarial-review/SKILL.md: To **run** it, use `"${DIFF[@]}"` (quoted, no word-splitting).
  • .agents/skills/adversarial-review/SKILL.md: Run `"${DIFF[@]}"`.
  • .agents/skills/adversarial-review/SKILL.md: `RUN=$(mktemp -d)` — scratch dir for the other model's output.
  • .agents/skills/adversarial-review/SKILL.md: **The other model's pass** — run, from the repo root, the row that matches you:
  • .agents/skills/adversarial-review/SKILL.md: # You are Claude → run Codex:
  • .agents/skills/adversarial-review/SKILL.md: -o "$RUN/other_findings.json" \
  • .agents/skills/adversarial-review/SKILL.md: # You are Codex → run Claude (read-only via plan mode; parse the JSON block it returns):
  • .agents/skills/adversarial-review/SKILL.md: $(cat "$SKILL_DIR/schemas/findings.schema.json")" </dev/null > "$RUN/other_raw.json"
  • .agents/skills/fix-pr-issues/SKILL.md: Run the smallest meaningful verification first, then widen as needed.
  • .agents/skills/fix-pr-issues/SKILL.md: Commit changed code or documentation with `git commit -s`.
  • .agents/skills/fix-pr-issues/SKILL.md: For each addressed comment or blocker, reply with the fix commit, verification run, and current Codex gate status.
  • .agents/skills/infographics/SKILL.md: uv run --script scripts/generate_pr_infographic.py \
  • .agents/skills/infographics/SKILL.md: uv run --script scripts/generate_pr_infographic.py \
  • .agents/skills/infographics/SKILL.md: `--dry-run` is an alias for `--print-prompt`;
  • .agents/skills/infographics/SKILL.md: changed-file orientation: `git diff --stat` plus key file reads
  • .agents/skills/infographics/SKILL.md: uv run --script scripts/generate_infographic.py \
  • .agents/skills/instrumentation/SKILL.md: The reason this skill exists is that Claude tends to get a few things subtly wrong with Logfire - especially the ordering of `configure()` vs `instrument_*()` calls, the structured logging syntax, and which extras to install.
  • .agents/skills/instrumentation/SKILL.md: Install `logfire` with extras matching the detected frameworks.
  • .agents/skills/instrumentation/SKILL.md: uv add 'logfire[pydantic-ai]'
  • .agents/skills/instrumentation/SKILL.md: For PydanticAI, each agent run becomes a parent span containing child spans for every tool call and LLM request.
  • .agents/skills/instrumentation/SKILL.md: Launch with: `node --require ./instrumentation.js app.js`
  • .agents/skills/instrumentation/SKILL.md: Run `logfire auth` to check authentication (or set `LOGFIRE_TOKEN`)
  • .agents/skills/pr-create/SKILL.md: Return the PR URL, current head SHA, validation run, check status, and Codex gate evidence.
  • .agents/skills/pr-description/SKILL.md: git log --oneline --decorate -n 10
  • .agents/skills/pr-description/SKILL.md: Testing section must include exact commands run and outcomes.
  • .agents/skills/pr-review-loop/SKILL.md: If the comment identifies a real issue, patch it, run focused validation, push, and restart the loop on the new head.
  • .agents/skills/pr-review-loop/SKILL.md: Only run `gh pr merge` when the gate is `approved` or `overridden` and tests are passing on that same head.
  • .agents/skills/pull-request/SKILL.md: After activation, run Python scripts as `python ...`.
  • .agents/skills/pull-request/SKILL.md: For one-off commands where activation is awkward, prefer `./.venv/bin/python ...` or the repo's `uv run ...` patterns.
  • .agents/skills/pull-request/SKILL.md: Run focused tests for the changed surface.
  • .agents/skills/pull-request/SKILL.md: Run the repo's required gate, such as `just fast-check` for source changes or `just package-check` for agent/package changes, before calling the branch ready.
  • .agents/skills/pull-request/SKILL.md: `Testing`: exact commands run and whether they passed.
  • .agents/skills/pull-request/SKILL.md: If the feedback is correct and in scope, patch, run focused validation, push, and restart the loop on the new head.
  • .agents/skills/pythonic-code/SKILL.md: Run the narrowest command that proves the change, then widen according to risk:
  • .agents/skills/pythonic-code/evals/context/AGENTS.md: Run the focused tests under `evals/files` and the configured Ruff checks for changed Python.
  • .claude/commands/release/beta.md: When the user runs `/beta`, execute the following steps:
  • .claude/commands/release/beta.md: While `pyproject.toml` pins a FastMCP pre-release (`fastmcp==X.Y.Zb1`), `just beta` refuses to run: every documented install passes `--prerelease=allow`, which uv applies to basic-memory itself, so a beta on PyPI would become the default install for stable users (#1338).
  • .claude/commands/release/beta.md: Execute the automated beta release process:
  • .claude/commands/release/beta.md: Test beta installation: `uv tool install basic-memory --pre`
  • .claude/commands/release/beta.md: # Install/upgrade to beta
  • .claude/commands/release/beta.md: uv tool install basic-memory --pre
  • .claude/commands/release/beta.md: uv tool upgrade basic-memory --prerelease=allow
  • .claude/commands/release/beta.md: Install/test with:
  • .claude/commands/release/beta.md: uv tool install basic-memory --pre
  • .claude/commands/release/beta.md: **Test features**: Install and validate new functionality
  • .claude/commands/release/changelog.md: When the user runs `/changelog`, execute the following steps:
  • .claude/commands/release/changelog.md: git tag -l "v*" --sort=-version:refname | grep -v "b\|rc" | head -1
  • .claude/commands/release/changelog.md: git log --oneline ${last_tag}..HEAD
  • .claude/commands/release/changelog.md: uv tool install basic-memory --prerelease=allow
  • .claude/commands/release/release-check.md: When the user runs `/release-check`, execute the following validation steps:
  • .claude/commands/release/release-check.md: 2. Run `/release v0.13.0` when ready
  • .claude/commands/release/release-check.md: Can be run multiple times safely
  • .claude/commands/release/release.md: When the user runs `/release`, execute the following steps:
  • .claude/commands/release/release.md: Execute the automated release process:
  • .claude/commands/release/release.md: ✅ Builds the package using `uv build`
  • .claude/commands/release/release.md: Test installation: `uv tool install basic-memory --prerelease=allow`
  • .claude/commands/release/release.md: Test Homebrew installation: `brew install basicmachines-co/basic-memory/basic-memory`
  • .claude/commands/release/release.md: gh workflow run mcp-registry-publish.yml
  • .claude/commands/release/release.md: curl "https://registry.modelcontextprotocol.io/v0.1/servers?search=basic-memory" · uses the network
  • .claude/commands/release/release.md: Pull latest from GitHub: `git pull origin main` · uses the network
  • .claude/commands/release/release.md: Create release branch: `git checkout -b release/v{VERSION}`
  • .claude/commands/release/release.md: Commit (`git commit -s -m "..."`), push, and open a PR against `basicmachines-co/basicmemory.com`
  • .claude/commands/release/release.md: Pull latest from GitHub: `git pull origin main` · uses the network
  • .claude/commands/release/release.md: Create release branch: `git checkout -b release/v{VERSION}`
  • .claude/commands/release/release.md: Commit: `git commit -s -m "docs: add v{VERSION} release notes"`
  • .claude/commands/release/release.md: Install with pip/uv:
  • .claude/commands/release/release.md: uv tool install basic-memory --prerelease=allow
  • .claude/commands/release/release.md: Install with Homebrew:
  • .claude/commands/release/release.md: brew install basicmachines-co/basic-memory/basic-memory
  • .claude/commands/release/release.md: uv tool upgrade basic-memory --prerelease=allow
  • .claude/commands/release/release.md: To bump only the plugin/agent artifacts out of band, use `just set-packages-version <version>` (preview with `just set-packages-version-dry-run <version>`).
  • .claude/commands/spec.md: Execute the spec command: `/spec $ARGUMENTS`
  • .claude/commands/test-live.md: Execute comprehensive real-world testing of Basic Memory using the installed version.
  • .claude/commands/test-live.md: `phase` (optional): Specific test phase to run (`recent`, `core`, `features`, `edge`, `workflows`, `stress`, or `all`)
  • .claude/commands/test-live.md: When the user runs `/project:test-live`, execute comprehensive test plan:
  • .claude/commands/test-live.md: Run `git log --oneline -20` to examine recent commits
  • .claude/commands/test-live.md: Run the bash `date` command to get the current date/time.
  • .claude/commands/test-live.md: Execute test scenarios systematically
  • AGENTS.md: Install: `just install` or `pip install -e ".[dev]"`
  • AGENTS.md: Run all tests (SQLite + Postgres): `just test`
  • AGENTS.md: Run all tests against SQLite: `just test-sqlite`
  • AGENTS.md: Run all tests against Postgres: `just test-postgres` (uses testcontainers)
  • AGENTS.md: Run unit tests (SQLite): `just test-unit-sqlite`
  • AGENTS.md: Run unit tests (Postgres): `just test-unit-postgres`
  • AGENTS.md: Run integration tests (SQLite): `just test-int-sqlite`
  • AGENTS.md: Run integration tests (Postgres): `just test-int-postgres`
  • AGENTS.md: Run impacted tests: `just fast-test` or `just testmon` (pytest-testmon;
  • AGENTS.md: Run MCP smoke test: `just test-smoke`
  • AGENTS.md: Run all consolidated agent package checks: `just package-check`
  • AGENTS.md: Run Claude Code plugin checks: `just package-check-claude-code`
  • AGENTS.md: Run shared skills checks: `just package-check-skills`
  • AGENTS.md: Run Hermes plugin checks: `just package-check-hermes`
  • AGENTS.md: Run OpenClaw plugin checks: `just package-check-openclaw`
  • AGENTS.md: Run host-native agent harness checks: `just agent-harness-check`
  • AGENTS.md: Run benchmarks: `pytest test-int/test_sync_performance_benchmark.py -v -m "benchmark and not slow"`
  • AGENTS.md: Type check: `just typecheck` or `uv run ty check src tests test-int`
  • AGENTS.md: Type check (pyright): `just typecheck-pyright` or `uv run pyright`
  • AGENTS.md: Format: `just format` or `uv run ruff format .`
  • AGENTS.md: Run all static code checks: `just check` (runs lint, format, typecheck)
  • AGENTS.md: Run development MCP Inspector: `just run-inspector`
  • AGENTS.md: **Test:** `just fast-test` for pytest-testmon impacted tests, or a targeted `uv run pytest ...` command.
  • AGENTS.md: Run `just test-smoke` when you specifically need the MCP smoke flow.
  • AGENTS.md: If testmon is “cold,” the first run may be long.
  • AGENTS.md: `just package-check-openclaw` — runs the OpenClaw package install, copies top-level skills into the generated bundle, typechecks, lints, builds `dist/`, runs Bun tests, and performs `npm pack --dry-run`.
  • AGENTS.md: Before opening or updating a PR, run the checks that mirror the common required CI failures:
  • AGENTS.md: Run `just typecheck` in addition to targeted `ruff` and `pytest` commands when tests were added or changed.
  • AGENTS.md: Sign commits with `git commit -s` so DCO passes.
  • AGENTS.md: Add or update meaningful regression tests for bugs and risky behavior, prefer real code paths over mocks, and run the narrowest command that proves the change before widening verification.
  • AGENTS.md: connection.execute("PRAGMA journal_mode=WAL")
  • AGENTS.md: By default, tests run against SQLite (fast, no Docker needed)
  • AGENTS.md: Set `BASIC_MEMORY_TEST_POSTGRES=1` to run against Postgres (uses testcontainers - Docker required)
  • AGENTS.md: The recipes bump version metadata, run pre-flight checks, land the bump on `main` through a release PR, tag, and push the tag.
  • AGENTS.md: PyPI consumers install with `pip install basic-memory --pre`.
  • AGENTS.md: The recipe refuses a beta whenever `pyproject.toml` pins a FastMCP pre-release (`fastmcp==X.Y.ZbN`): installs then need `--prerelease=allow`, which uv also applies to basic-memory itself, so a beta on PyPI would become the default install for stable users.
  • AGENTS.md: **Release dry run:** `just release-dry-run v0.21.4` previews the consolidated version update without writing files.
  • AGENTS.md: **Development builds are not published to PyPI.** Documented installs pass `--prerelease=allow` (published releases through v0.23.2 pin a FastMCP pre-release), and uv applies that flag to basic-memory itself, so a `.devN` build on PyPI would outrank the stable release for every fresh install.
  • AGENTS.md: To try unreleased `main`, install from git: `uv tool install "basic-memory @ git+https://github.com/basicmachines-co/basic-memory" --prerelease=allow`.
  • AGENTS.md: **Post-release tasks** the recipe surfaces but doesn't run:
  • AGENTS.md: MCP Registry — after the version is live on PyPI, dispatch `.github/workflows/mcp-registry-publish.yml` (`gh workflow run mcp-registry-publish.yml`);
  • CLAUDE.md: Install: `just install` or `pip install -e ".[dev]"`
  • CLAUDE.md: Run all tests (SQLite + Postgres): `just test`
  • CLAUDE.md: Run all tests against SQLite: `just test-sqlite`
  • CLAUDE.md: Run all tests against Postgres: `just test-postgres` (uses testcontainers)
  • CLAUDE.md: Run unit tests (SQLite): `just test-unit-sqlite`
  • CLAUDE.md: Run unit tests (Postgres): `just test-unit-postgres`
  • CLAUDE.md: Run integration tests (SQLite): `just test-int-sqlite`
  • CLAUDE.md: Run integration tests (Postgres): `just test-int-postgres`
  • CLAUDE.md: Run impacted tests: `just fast-test` or `just testmon` (pytest-testmon;
  • CLAUDE.md: Run MCP smoke test: `just test-smoke`
  • CLAUDE.md: Run all consolidated agent package checks: `just package-check`
  • CLAUDE.md: Run Claude Code plugin checks: `just package-check-claude-code`
  • CLAUDE.md: Run shared skills checks: `just package-check-skills`
  • CLAUDE.md: Run Hermes plugin checks: `just package-check-hermes`
  • CLAUDE.md: Run OpenClaw plugin checks: `just package-check-openclaw`
  • CLAUDE.md: Run host-native agent harness checks: `just agent-harness-check`
  • CLAUDE.md: Run benchmarks: `pytest test-int/test_sync_performance_benchmark.py -v -m "benchmark and not slow"`
  • CLAUDE.md: Type check: `just typecheck` or `uv run ty check src tests test-int`
  • CLAUDE.md: Type check (pyright): `just typecheck-pyright` or `uv run pyright`
  • CLAUDE.md: Format: `just format` or `uv run ruff format .`
  • CLAUDE.md: Run all static code checks: `just check` (runs lint, format, typecheck)
  • CLAUDE.md: Run development MCP Inspector: `just run-inspector`
  • CLAUDE.md: **Test:** `just fast-test` for pytest-testmon impacted tests, or a targeted `uv run pytest ...` command.
  • CLAUDE.md: Run `just test-smoke` when you specifically need the MCP smoke flow.
  • CLAUDE.md: If testmon is “cold,” the first run may be long.
  • CLAUDE.md: `just package-check-openclaw` — runs the OpenClaw package install, copies top-level skills into the generated bundle, typechecks, lints, builds `dist/`, runs Bun tests, and performs `npm pack --dry-run`.
  • CLAUDE.md: Before opening or updating a PR, run the checks that mirror the common required CI failures:
  • CLAUDE.md: Run `just typecheck` in addition to targeted `ruff` and `pytest` commands when tests were added or changed.
  • CLAUDE.md: Sign commits with `git commit -s` so DCO passes.
  • CLAUDE.md: Add or update meaningful regression tests for bugs and risky behavior, prefer real code paths over mocks, and run the narrowest command that proves the change before widening verification.
  • CLAUDE.md: connection.execute("PRAGMA journal_mode=WAL")
  • CLAUDE.md: By default, tests run against SQLite (fast, no Docker needed)
  • CLAUDE.md: Set `BASIC_MEMORY_TEST_POSTGRES=1` to run against Postgres (uses testcontainers - Docker required)
  • CLAUDE.md: The recipes bump version metadata, run pre-flight checks, land the bump on `main` through a release PR, tag, and push the tag.
  • CLAUDE.md: PyPI consumers install with `pip install basic-memory --pre`.
  • CLAUDE.md: The recipe refuses a beta whenever `pyproject.toml` pins a FastMCP pre-release (`fastmcp==X.Y.ZbN`): installs then need `--prerelease=allow`, which uv also applies to basic-memory itself, so a beta on PyPI would become the default install for stable users.
  • CLAUDE.md: **Release dry run:** `just release-dry-run v0.21.4` previews the consolidated version update without writing files.
  • CLAUDE.md: **Development builds are not published to PyPI.** Documented installs pass `--prerelease=allow` (published releases through v0.23.2 pin a FastMCP pre-release), and uv applies that flag to basic-memory itself, so a `.devN` build on PyPI would outrank the stable release for every fresh install.
  • CLAUDE.md: To try unreleased `main`, install from git: `uv tool install "basic-memory @ git+https://github.com/basicmachines-co/basic-memory" --prerelease=allow`.
  • CLAUDE.md: **Post-release tasks** the recipe surfaces but doesn't run:
  • CLAUDE.md: MCP Registry — after the version is live on PyPI, dispatch `.github/workflows/mcp-registry-publish.yml` (`gh workflow run mcp-registry-publish.yml`);
  • benchmarks/AGENTS.md: Install: `uv sync --group dev`
  • benchmarks/AGENTS.md: Run tests: `uv run pytest -q`
  • benchmarks/AGENTS.md: Lint: `uv run ruff check .`
  • benchmarks/AGENTS.md: Type check: `uv run pyright`
  • benchmarks/AGENTS.md: `uv run pytest -q`
  • benchmarks/AGENTS.md: `uv run ruff check .`
  • benchmarks/AGENTS.md: `uv run pyright`
  • benchmarks/AGENTS.md: CLI entrypoint: `uv run bm-bench ...`
  • benchmarks/AGENTS.md: `uv run bm-bench datasets fetch --dataset locomo`
  • benchmarks/AGENTS.md: `uv run bm-bench convert locomo --dataset-path benchmarks/datasets/locomo/locomo10.json --output-dir benchmarks/generated/locomo`
  • benchmarks/AGENTS.md: `bash benchmarks/datasets/beam/download.sh` (BEAM data is never vendored;
  • benchmarks/AGENTS.md: `uv run bm-bench convert beam --tier 100K --output-dir benchmarks/generated/beam-100k`
  • benchmarks/AGENTS.md: Run retrieval:
  • benchmarks/AGENTS.md: `uv run bm-bench run retrieval --providers bm-local,mem0-local --dataset-id locomo --dataset-path benchmarks/datasets/locomo/locomo10.json --corpus-dir benchmarks/generated/locomo/docs --queries-path benchmarks/generated/locomo/queries.json --output-root benchmarks/runs --allow-provider-skip`
  • benchmarks/AGENTS.md: Run end-to-end QA scoring:
  • benchmarks/AGENTS.md: `uv run bm-bench run qa --run-dir benchmarks/runs/<run-id> --answerer claude:claude-haiku-4-5 --judge claude:claude-sonnet-4-6`
  • benchmarks/AGENTS.md: BEAM nugget scoring (post-hoc, after `run qa` on a BEAM run):
  • benchmarks/AGENTS.md: `uv run bm-bench run beam-score --run-dir benchmarks/runs/<run-id> --judge claude:claude-sonnet-4-6`
  • benchmarks/AGENTS.md: `uv run bm-bench run agent-tasks --surfaces bm --model openai-compat:<model>@<base_url> --bm-local-path <bm-checkout>`
  • benchmarks/AGENTS.md: `uv run bm-bench validate-artifacts --run-dir benchmarks/runs/<run-id>`
  • benchmarks/AGENTS.md: `uv run bm-bench publish --run-dir benchmarks/runs/<run-id> --destination benchmarks/results/public`
  • benchmarks/AGENTS.md: `just bench-run-beam-100k`
  • benchmarks/AGENTS.md: `just bench-beam-score benchmarks/runs/<run-id>`
  • benchmarks/AGENTS.md: `just bench-run-bm-local`
  • benchmarks/AGENTS.md: `just bench-run-mem0-local`
  • benchmarks/AGENTS.md: `just bench-run-full`
  • benchmarks/AGENTS.md: `just bench-qa benchmarks/runs/<run-id>`
  • benchmarks/AGENTS.md: `just bench-publish benchmarks/runs/<run-id>`
  • benchmarks/AGENTS.md: `src/basic_memory_benchmarks/runner.py` - run orchestration
  • benchmarks/AGENTS.md: `benchmarks/runs/` - raw run artifacts
  • benchmarks/AGENTS.md: The benchmark command is typically invoked through `uv run ...` so `.venv/bin/bm` is used.
  • benchmarks/AGENTS.md: Ingest and search use a stable benchmark `user_id` namespace per run.
  • benchmarks/AGENTS.md: Prefer setting only required credentials for run reproducibility.
  • benchmarks/AGENTS.md: Always publish conversion code and run artifacts.
  • benchmarks/AGENTS.md: Sign commits: `git commit -s`.
  • integrations/hermes/skill/SKILL.md: **Search before answering.** If the user asks "what did we decide about X?", run `bm_search` first.
  • integrations/openclaw/AGENTS.md: **Build output** — `bun run build` emits `dist/` for `runtimeExtensions`;
  • integrations/openclaw/AGENTS.md: `scripts/bm-local.sh` runs BM from the monorepo root via `uv run --project ...` when available, then falls back to `bm` on PATH
  • integrations/openclaw/AGENTS.md: **Package CI** (root `.github/workflows/consolidated-packages.yml`): validates skills, typechecks, lints, builds, tests, and runs `npm pack --dry-run`.
  • integrations/openclaw/CLAUDE.md: **Build output** — `bun run build` emits `dist/` for `runtimeExtensions`;
  • integrations/openclaw/CLAUDE.md: `scripts/bm-local.sh` runs BM from the monorepo root via `uv run --project ...` when available, then falls back to `bm` on PATH
  • integrations/openclaw/CLAUDE.md: **Package CI** (root `.github/workflows/consolidated-packages.yml`): validates skills, typechecks, lints, builds, tests, and runs `npm pack --dry-run`.
  • integrations/pi/skills/basic-memory-pi-setup/SKILL.md: If the user wants MCP mode, install the adapter and switch transport:
  • integrations/pi/skills/basic-memory-pi-setup/SKILL.md: pi install npm:pi-mcp-adapter
  • integrations/pi/skills/basic-memory-pi-setup/SKILL.md: Run `/bm-status` and check the effective auto recall/capture state, then `/bm-recall setup` or `/bm-capture Pi setup checkpoint` to verify the path.
  • integrations/pi/skills/basic-memory-pi-setup/SKILL.md: For local Basic Memory development in a trusted workspace, set `BASIC_MEMORY_PI_TRUST_BM_COMMAND=1` and use `bmCommand` as an argv array such as `["uv", "run", "--project", "/path/to/basic-memory", "basic-memory"]`;
  • integrations/tau/skills/basic-memory-setup/SKILL.md: Locate the integration directory: the installed `~/.tau/extensions/basic-memory` from `bm install tau`, or `integrations/tau` in an explicitly identified Basic Memory checkout.
  • integrations/tau/skills/basic-memory-setup/SKILL.md: A packaged install does not require a source checkout.
  • integrations/tau/skills/basic-memory-setup/SKILL.md: If the extension is loaded, ask the user to run `/bm-status`.
  • integrations/tau/skills/basic-memory-setup/SKILL.md: A text reply does not run a slash command or control the current Tau session.
  • integrations/tau/skills/basic-memory-setup/SKILL.md: Consult current Basic Memory install docs rather than guessing package versions or changing the user's global Tau installation.
  • integrations/tau/skills/basic-memory-setup/SKILL.md: For a packaged install, with approval for dependency installation, use:
  • integrations/tau/skills/basic-memory-setup/SKILL.md: bm install tau --sync
  • integrations/tau/skills/basic-memory-setup/SKILL.md: Then give the user this command to run in their terminal:
  • integrations/tau/skills/basic-memory-setup/SKILL.md: uv run --project ~/.tau/extensions/basic-memory tau
  • integrations/tau/skills/basic-memory-setup/SKILL.md: For source development, with approval, run `uv sync --project <integration-directory>` and launch `uv run --project <integration-directory> tau -e <integration-directory>`.
  • integrations/tau/skills/basic-memory-setup/SKILL.md: `bm install tau` installs this setup skill and the prompt templates separately;
  • plugins/claude-code/skills/bm-checkpoint/SKILL.md: `git status --short`
  • plugins/claude-code/skills/bm-checkpoint/SKILL.md: tests or checks actually run
  • plugins/claude-code/skills/bm-checkpoint/SKILL.md: `## Verification`, for checks actually run and their outcomes
  • plugins/claude-code/skills/bm-orient/SKILL.md: If no config is present, continue against the default Basic Memory project and mention that setup has not been run.
  • plugins/claude-code/skills/bm-setup/SKILL.md: Run a short, adaptive interview (~2-3 minutes) and then write the configuration.
  • plugins/claude-code/skills/bm-setup/SKILL.md: Install it: `uv tool install basic-memory --prerelease=allow` (or `pip install basic-memory`), a version exposing the 1.0 `bm_*` tools.
  • plugins/claude-code/skills/bm-setup/SKILL.md: A purely local server (`uvx --prerelease=allow basic-memory mcp`) treats the path as a local directory and fails to create it (e.g. read-only `/`).
  • plugins/claude-code/skills/bm-setup/SKILL.md: Run `bm_project_list()`.
  • plugins/claude-code/skills/bm-setup/SKILL.md: Inspect it: `bm_list(path="/", project="<primaryProject>")` for the top-level folder layout (`bm_find` for recursive discovery), sample a few notes per folder (and, where a folder holds recurring typed notes, you may run `bm_schema_infer()` to see their shape).
  • plugins/claude-code/skills/bm-setup/SKILL.md: (This is the single knob for how proactive the assistant is — the hooks always run regardless.)
  • plugins/claude-code/skills/bm-setup/SKILL.md: I can install them alongside this plugin." These are the canonical, framework-agnostic skills (the same set OpenClaw bundles).
  • plugins/claude-code/skills/bm-setup/SKILL.md: (See "Install the shared skills" below.)
  • plugins/claude-code/skills/bm-setup/SKILL.md: **First, guard against clobbering a source checkout.** If `./skills` already exists, is tracked in git, and holds `memory-*` directories, you're inside the skills' own source repo (e.g. `basic-memory` itself) — the install would overwrite the working copy with published versions.
  • plugins/claude-code/skills/bm-setup/SKILL.md: In that case **skip the install** and tell the user the skills are already present as source;
  • plugins/claude-code/skills/bm-setup/SKILL.md: Otherwise, run:
  • plugins/claude-code/skills/bm-setup/SKILL.md: If `npx` / the `skills` CLI isn't available, point the user at the manual install in the top-level [`skills/README.md`](../../../../skills/README.md).
  • plugins/claude-code/skills/bm-setup/SKILL.md: Writing the `basicMemory` block is also what stops the SessionStart hook's first-run nudge — the config's presence is the signal that setup has run.
  • plugins/claude-code/skills/bm-setup/SKILL.md: Use the CLI the hook uses (`basic-memory` / `bm` / `uvx --prerelease=allow basic-memory`).
  • plugins/claude-code/skills/bm-setup/SKILL.md: **Primary:** run the open-decision query the SessionStart hook runs against `primaryProject`: `… tool search --note-types decision --filters '{"status": "open"}' --page-size 5 --project <primaryProject>`.
  • plugins/claude-code/skills/bm-setup/SKILL.md: **Hook health:** run `basic-memory hook status --harness claude --project-dir <project-root>` with the first available `basic-memory`, `bm`, or `uvx --prerelease=allow basic-memory` launcher.
  • plugins/claude-code/skills/bm-setup/SKILL.md: the hooks already run.
  • plugins/claude-code/skills/bm-setup/SKILL.md: Run `/basic-memory:bm-status` anytime to see what I'm tracking."*
  • plugins/claude-code/skills/bm-status/SKILL.md: **CLI reachable?** Run `basic-memory --version`, then `bm --version`, then `uvx --prerelease=allow basic-memory --version`.
  • plugins/claude-code/skills/bm-status/SKILL.md: **Core hook health.** With the first available launcher, run `basic-memory hook status --harness claude --project-dir <project-root>`.
  • plugins/codex/skills/bm-checkpoint/SKILL.md: `git status --short`
  • plugins/codex/skills/bm-checkpoint/SKILL.md: tests or checks actually run
  • plugins/codex/skills/bm-checkpoint/SKILL.md: `## Verification`, for checks actually run and their outcomes
  • plugins/codex/skills/bm-orient/SKILL.md: Mention that setup has not been run.
  • plugins/codex/skills/bm-orient/SKILL.md: Run the `coding_session` topic search separately and include it only when `sessionProfile=coding` and the configured `repository` is present.
  • plugins/codex/skills/bm-setup/SKILL.md: If MCP tools are not available, run `basic-memory --version` or `bm --version`.
  • plugins/codex/skills/bm-setup/SKILL.md: If neither works, stop and tell the user to install Basic Memory and connect the MCP server.
  • plugins/codex/skills/bm-setup/SKILL.md: The plugin bundles an `.mcp.json` that starts `uvx --prerelease=allow basic-memory mcp`.
  • plugins/codex/skills/bm-setup/SKILL.md: `checkpointOnCompact`: whether post-compaction SessionStart asks Codex to run `bm-checkpoint`.
  • plugins/codex/skills/bm-setup/SKILL.md: Run `basic-memory hook status --harness codex --project-dir <repo-root>` (using `bm` or `uvx --prerelease=allow basic-memory` if needed).
  • plugins/codex/skills/bm-setup/SKILL.md: Tell the user that plugin hooks need to be reviewed and trusted in Codex before they run.
  • plugins/codex/skills/bm-share/SKILL.md: If no team projects are configured, stop and ask the user to run setup or add a target.
  • plugins/codex/skills/bm-status/SKILL.md: fallback `uvx --prerelease=allow basic-memory --version`
  • plugins/codex/skills/bm-status/SKILL.md: with the first available launcher, run `basic-memory hook status --harness codex --project-dir <repo-root>`
  • plugins/codex/skills/bm-status/SKILL.md: check `uv --version` in the current environment independently of CLI reachability;
  • plugins/codex/skills/bm-status/SKILL.md: uv is a required hook prerequisite
  • plugins/codex/skills/bm-status/SKILL.md: remind the user that Codex plugin hooks must be reviewed and trusted before they run
  • skills/AGENTS.md: Skills can be installed via `npx skills add` or copied manually into any agent's skills directory.
  • skills/AGENTS.md: memory-agents/SKILL.md # Create, run, and check Basic Memory Cloud agents
  • skills/AGENTS.md: memory-doctor/SKILL.md # Run bm doctor, explain findings, and apply fixes with consent
  • skills/AGENTS.md: Run `just check` from `skills/` or `just package-check-skills` from the monorepo root to validate the `memory-*/SKILL.md` frontmatter before committing changes.
  • skills/CLAUDE.md: Skills can be installed via `npx skills add` or copied manually into any agent's skills directory.
  • skills/CLAUDE.md: memory-agents/SKILL.md # Create, run, and check Basic Memory Cloud agents
  • skills/CLAUDE.md: memory-doctor/SKILL.md # Run bm doctor, explain findings, and apply fixes with consent
  • skills/CLAUDE.md: Run `just check` from `skills/` or `just package-check-skills` from the monorepo root to validate the `memory-*/SKILL.md` frontmatter before committing changes.
  • skills/memory-agents/SKILL.md: Agents run in Basic Memory Cloud only, on plans that include them.
  • skills/memory-agents/SKILL.md: Asked to create, change, run, or turn off an agent
  • skills/memory-agents/SKILL.md: Asked how an agent run went, what it changed, or why it did not run
  • skills/memory-agents/SKILL.md: with `agent`, whether that agent can run | | `bm_agent_run(agent="<agent>", project="<project>")` | Starts an agent on a note (`identifier`), a folder, or nothing;
  • skills/memory-agents/SKILL.md: returns the run id | | `bm_agent_get(run_id="<run id>")` | One run: status, notes changed, and the agent's last reply;
  • skills/memory-agents/SKILL.md: `whole_workspace=True` lists every run waiting for review | | `bm_agent_mark(decision="kept", run_id="<run id>")` | Mark a run `kept` or `dismissed`;
  • skills/memory-agents/SKILL.md: with no `run_id`, `kept` keeps every waiting run |
  • skills/memory-agents/SKILL.md: Read the meeting note you run on.
  • skills/memory-agents/SKILL.md: An agent changes notes only in its own project, and it runs only if both the person who last edited the agent note and the person the run is for can edit that project.
  • skills/memory-agents/SKILL.md: An agent note last edited by another agent cannot run.
  • skills/memory-agents/SKILL.md: **Ask for a reply.** The last reply is the run's summary: what it created, linked, or left alone, and anything it was unsure about.
  • skills/memory-agents/SKILL.md: **Keep each run small.** A run has about seven minutes, including startup.
  • skills/memory-agents/SKILL.md: | Agent | Run it on | |---|---| | Cleanup | A hub or project index note;
  • skills/memory-agents/SKILL.md: # -> run id. Runs usually take one to a few minutes.
  • skills/memory-agents/SKILL.md: bm_agent_get(run_id="<run id>", project="work")
  • skills/memory-agents/SKILL.md: Ask before running one, unless the user has just asked for that run.
  • skills/memory-agents/SKILL.md: `bm_agent_get(run_id="<run id>", project="<project>")` shows the status, the notes the run created, edited, moved, or deleted, and the agent's last reply.
  • skills/memory-agents/SKILL.md: Every reply is also kept in a run log note, `agents/runs/<agent> run <id>`.
  • skills/memory-agents/SKILL.md: A queued run may be waiting: for the target note to settle, for a free slot (a workspace runs a few agents at once), or for another run on the same note.
  • skills/memory-agents/SKILL.md: When a run is skipped, its reason says why:
  • skills/memory-agents/SKILL.md: the detail names the field | | `agent_disabled` | Set `enabled: true` | | `agent_changed` | The agent note changed after the run was queued;
  • skills/memory-agents/SKILL.md: run it again | | `agent_not_by_a_person` | A person, or an assistant acting for one, saves the agent note again | | `agent_removed`, `trigger_changed` | The agent note or the target note was deleted | | `instruction_author_has_no_access`, `requester_has_no_access` | That person needs a …[+123 chars]
  • skills/memory-agents/SKILL.md: A failed run says why as well: `timeout` (the run ran out of time;
  • skills/memory-agents/SKILL.md: give it a smaller job) or a model error (run it again).
  • skills/memory-capture/SKILL.md: **Always run the same-thread lookup** before deciding to create or update.
  • skills/memory-ci-capture/SKILL.md: Treat it as the immutable source of truth for repository, event type, PR number, workflow run, SHA, source URL, timestamps, and deployment environment.
  • skills/memory-ci-capture/SKILL.md: For production deploys, focus on what reached production, the deployed SHA, environment, workflow run, and verification evidence.
  • skills/memory-comark/SKILL.md: In Basic Memory Cloud, `bm_read(identifier="<note>", view="text", project="<project>")` returns the note as a reader sees it: every component as plain Markdown, with live queries run now.
  • skills/memory-comark/SKILL.md: Elsewhere, only the browser runs the query, so run the equivalent read yourself (for example `bm_search` with metadata filters;
  • skills/memory-doctor/SKILL.md: The fixes it suggests do change things, so run them only after the user agrees.
  • skills/memory-doctor/SKILL.md: Without `--skip-self-test`, doctor also runs a self-test: it writes, indexes and searches a note in a throwaway sandbox, which takes a few seconds and proves the install itself works.
  • skills/memory-doctor/SKILL.md: Run it when the report is clean but something still seems broken.
  • skills/memory-doctor/SKILL.md: Run the commands the user approves.
  • skills/memory-doctor/SKILL.md: Run `bm doctor --skip-self-test --json` again and confirm the findings are gone.
  • skills/memory-ingest/SKILL.md: **A file instead of pasted text.** For a PDF, Word, PowerPoint, or CSV file in the project, and if the `bm` CLI is available, run `bm import document <path>`.
  • skills/memory-literary-analysis/SKILL.md: The two rules that matter across a 100+ chapter run:
  • skills/memory-literary-analysis/SKILL.md: Store the map in the project (a note or a small JSON file) so later batches — and a resumed run after context compaction — do not have to rediscover it.
  • skills/memory-literary-analysis/SKILL.md: fix the spelling or add the alias, then re-run the chapter.
  • skills/memory-literary-analysis/SKILL.md: **Validate periodically.** Run `bm_schema_validate(project="<work-name>")` after each batch, not just at the end.
  • skills/memory-notes/SKILL.md: Day points run "from that date onward", so a due-date window also returns items that are already overdue.
  • skills/memory-okf/SKILL.md: With the `bm` CLI and a local project, you can run the export and check it:
  • skills/memory-okf/SKILL.md: Run `bm okf check` on a bundle, not on the project.
  • skills/memory-onboarding/SKILL.md: **Check the live docs when unsure.** Basic Memory's documentation is agent-readable: fetch `https://docs.basicmemory.com/llms.txt` for an index, and any page as clean markdown via its `raw/....md` URL (e.g. `raw/reference/mcp-tools-reference.md`, `raw/concepts/schema-system.md`). · uses the network
  • skills/memory-onboarding/SKILL.md: **Migrate existing notes** *(restructure path)* → execute the approved old→new mapping from Phase 2 before seeding anything: move each existing note to its new home, set its note type, add the observations its schema requires, and update indexes as notes land.
  • skills/memory-onboarding/SKILL.md: **Validate** → run `bm_schema_validate` on the seed notes AND any migrated notes;
  • skills/memory-onboarding/SKILL.md: Run short exercises:
  • skills/memory-quest/SKILL.md: When you tell the user to run Memory Quest again, use their host's form: `/memory-quest` in Claude Code, `$memory-quest` in Codex, or just asking for it in a chat app.
  • skills/memory-quest/SKILL.md: Tell the user to connect it and run Memory Quest again.
  • skills/memory-quest/SKILL.md: Tell the user to install the Basic Memory plugin for their assistant, or to save the memory routine from the Memory Quest panel in their assistant's instructions, then start a fresh conversation and run Memory Quest again.
  • skills/memory-quest/SKILL.md: Ask the user to open **https://app.basicmemory.com/memory-quest** and paste the code it shows. · uses the network
  • skills/memory-quest/SKILL.md: Say that the mission stays incomplete and they can run Memory Quest again any time.
  • skills/memory-quest/SKILL.md: When this machine has a local project with the same name as a cloud one, which is common because every local install creates `main`, a local Basic Memory server writes the note to the local copy however you address it, by name, workspace-qualified name, or ID.
  • skills/memory-quest/SKILL.md: If no project is listed as `cloud`, stop and tell the user to create one in Basic Memory Cloud (or connect their cloud account), then run Memory Quest again.
  • skills/memory-quest/SKILL.md: If Memory Quest still shows Mission 8 as current after a minute, the usual cause is an expired or replaced code: get a new code and run Memory Quest again.
  • skills/memory-schema/SKILL.md: **Run diff** to see current state: `bm_schema_diff(note_type="Meeting", project="<project>")`
  • skills/memory-tasks/SKILL.md: **Schema validation is your friend** — Run `bm_schema_validate(note_type="Task", project="<project>")` periodically to catch incomplete tasks

MCP servers (4)

  • README.md (basic-memory): uvx --prerelease=allow basic-memory mcp
  • README.md (basic-memory): uvx --prerelease=allow basic-memory mcp
  • plugins/chatgpt/.mcp.json (basic-memory): https://cloud.basicmemory.com/mcp · uses the network
  • plugins/codex/.mcp.json (basic-memory): uvx --prerelease=allow basic-memory mcp

Hooks (4)

  • plugins/claude-code/hooks/hooks.json (SessionStart): uv run --quiet --script "${CLAUDE_PLUGIN_ROOT}/hooks/session_start.py"
  • plugins/claude-code/hooks/hooks.json (PreCompact): uv run --quiet --script "${CLAUDE_PLUGIN_ROOT}/hooks/pre_compact.py"
  • plugins/codex/hooks/hooks.json (SessionStart): uv run --quiet --script "${PLUGIN_ROOT}/hooks/session_start.py"
  • plugins/codex/hooks/hooks.json (PreCompact): uv run --quiet --script "${PLUGIN_ROOT}/hooks/pre_compact.py"

Install scripts (1)

  • src/basic_memory/cli/commands/install.py: python src/basic_memory/cli/commands/install.py
  • Medium risk: runs-instruction-instruction-network (.claude/commands/release/release.md:106)
  • Medium risk: runs-instruction-instruction-network (.claude/commands/release/release.md:119)
  • Medium risk: runs-instruction-instruction-network (.claude/commands/release/release.md:135)
  • Medium risk: runs-mcp-server-unpinned-runner (README.md:284)
  • Medium risk: runs-mcp-server-unpinned-runner (README.md:340)
  • Medium risk: runs-mcp-server-unpinned-runner (plugins/codex/.mcp.json)
  • Medium risk: runs-instruction-instruction-network (skills/memory-onboarding/SKILL.md:66)
  • Low risk: network-instructions (AGENTS.md:17)
  • Low risk: network-instructions (CLAUDE.md:17)
  • Low risk: scripts-present (plugins/claude-code/hooks/pre_compact.py)
  • Low risk: scripts-present (plugins/claude-code/hooks/session_start.py)
  • Low risk: network-instructions (plugins/claude-code/skills/bm-setup/SKILL.md:24)
  • Low risk: scripts-present (plugins/codex/hooks/pre_compact.py)
  • Low risk: scripts-present (plugins/codex/hooks/session_start.py)
  • Low risk: scripts-present (src/basic_memory/cli/commands/install.py)

Attribution and licence

Created by
Basic Machines
Declared authors
  • Basic Machines (declared in pyproject.toml)
  • Paul Hernandez (declared in CITATION.cff)
Publisher
Basic Machines (Official Basic Machines project)
Source
basicmachines-co/basic-memory · commit 370ae9d
Licence
GNU Affero General Public License v3.0 only (files served here)
  • ATTRIBUTION.md (written by AutoGineer)
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Install from source

461 of its files are not served here, so there is no ZIP. basicmachines-co/basic-memory at 370ae9d