Bm Writing logo

Bm Writing

OrganizationPopular
basicmachines-co
bm-writing

Apply the user-customizable writing standard for Basic Memory notes created or substantially revised by Codex. Use with bm-checkpoint, bm-decide, bm-remember, and other Basic Memory note-writing workflows.

Overview

Publisherbasicmachines-co
Repositorybasic-memory
Skill namebm-writing
Stars
4K
Forks
283
Bundled files
2
LicenseAGPL-3.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by basicmachines-co on GitHub. Read the source before you install it.

Installation

Install the Bm Writing AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/basicmachines-co/basic-memory.git /tmp/basic-memory
mkdir -p .claude/skills
cp -r /tmp/basic-memory/plugins/codex/skills/bm-writing .claude/skills/bm-writing
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Bm Writing in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Bm Writing on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Bm Writing is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Write Useful Project Memory

Use this shared standard whenever a Codex Basic Memory skill writes or substantially revises a note. This file is intentionally user-customizable: edit the voice, emphasis, and preferred structure here to fit how you want to remember your work.

Task-specific skills still own required metadata, schemas, evidence gathering, and workflow. This skill shapes the note; it never overrides factual constraints.

Voice

  • Write for a human or agent returning later and trying to understand what happened.
  • Be clear, direct, warm, and technically honest.
  • Prefer concrete observations over generic praise.
  • Have a point of view when the evidence supports it. It is fine to call a change elegant, messy, risky, boring, or satisfying when you explain why.
  • Keep personality in service of memory, not performance.

Tell The Story

  • Give the note a narrative spine: problem -> approach -> current state and impact.
  • Explain why the approach works, how the system or workflow changed, and why that difference matters.
  • Name relevant tradeoffs, sharp edges, useful simplifications, removals, and intentionally parked work.
  • Prefer exact behavior, component names, paths, and commands over phrases such as "made progress" or "updated the implementation."
  • Use substantive prose for context and reasoning. Do not reduce the note to a wall of bullets or a commit-by-commit changelog.
  • Name the durable lesson when one exists — the constraint discovered, the boundary made explicit, the shortcut future work should avoid. That is the part that turns a status report into project memory.
  • Match depth to the subject. A small remembered fact should remain small.

Anchor The Work

  • When the note records repository work, capture where that work lives: the project or repo, the git branch, and the PR or issue — plus the commit sha when a specific commit matters.
  • Put anchors the note's schema defines in frontmatter; record the rest as observations, e.g. - [branch] feat/bm-writing or - [pr] #1123.
  • Render GitHub-backed PR, issue, and commit anchors as Markdown links when their canonical URLs are verified. Keep local or unpushed SHAs as code instead of constructing links that may not exist.
  • Only anchor what is relevant. A remembered fact with no repo context needs no git anchors at all.

Preserve The Semantic Layer

  • Distill durable facts under ## Observations as - [category] fact.
  • Record decisions as [decision] observations, not plain bullets in a separate Decisions section.
  • Put graph edges under ## Relations using - relation_type [[Target Note]]. Never represent a relation as an observation such as [relates_to].
  • Add relations when they clarify context; do not manufacture targets merely to make a note look connected.

Evidence Boundary

  • Do not invent intent, impact, verification, decisions, or drama.
  • State uncertainty and missing evidence plainly.
  • Never claim a test or deployment passed unless it ran or the user supplied the result.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Bm Writing AI skill do?

Apply the user-customizable writing standard for Basic Memory notes created or substantially revised by Codex. Use with bm-checkpoint, bm-decide, bm-remember, and other Basic Memory note-writing workflows.

Why use Bm Writing on TypingMind?

Because you install it once and use it with any model. Bm Writing is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Bm Writing in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/basicmachines-co/basic-memory/tree/main/plugins/codex/skills/bm-writing. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Bm Writing?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Bm Writing?

As many as you like. As long as a model supports skills, you can use Bm Writing with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Bm Writing AI skill free?

Yes. It is published on GitHub by basicmachines-co under the AGPL-3.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇