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A pattern for building personal knowledge bases using LLMs.
This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.
Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.
A zero-dependency logging proxy that sits between Claude Code and the Anthropic API. It forwards every request untouched, streams the reply straight back (so the CLI is unaffected), and writes a readable Markdown document for each request — led by a ranked table of what is eating your context.
Your ultimate resource for macOS Office installers, serializers, and troubleshooting.
| name | govuk-style | |||||||
|---|---|---|---|---|---|---|---|---|
| description | Write and edit in GOV.UK / GDS house style — plain English, active voice, front-loaded content, sentence case, and no bold or italics for emphasis. Use when writing or editing reports, research write-ups, guidance, documentation, summaries, or any prose where clarity and accessibility matter. | |||||||
| user-invokable | true | |||||||
| args |
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