ContextCake Pack

Everything your agent needs to use ContextCake.

Drop this pack into your project so your AI assistant understands ContextCake — the architecture, the OKF format, the resolver, the MCP tools — and can actually help you wire it in, instead of guessing.

Files
28 source files
Folders
7 directories
Format
Markdown first
Accuracy
Current model only
  • What ContextCake is and the mental model
  • Architecture: sources, resolver, merge, conflicts
  • Install, first cascade, and writing a layer
  • MCP tools and connecting an AI agent

The arc

From zero to connected.

The pack is ordered the way you actually adopt ContextCake — understand it, run it, author for it, then hand it to your agent.

  1. Understand

    What ContextCake is, the layer cake, and how higher layers win per section — the mental model in a few files.

  2. Install

    Get the dependency-free engine running on Node 18+ and resolve your first cascade.

  3. Write a layer

    Author OKF concepts — frontmatter plus anchored sections — that team and personal layers can override.

  4. Connect an agent

    Run the MCP server and point Claude, Cursor, or any MCP client at the resolved graph.

Look inside

Open the pack.

File tree on the left, rendered markdown on the right — toggle to source any time. Start with the featured files for the quick read.

treecontextcake

Preview

START-HERE.md

Start Here

This is the ContextCake context pack — everything an AI agent (or a new developer) needs to actually use ContextCake in a project: what it is, how it’s built, and how to wire it into your own work.

Drop this pack into your repo, upload it to your AI tool, or install it as a Claude Code plugin. Then your assistant can answer “how do I use ContextCake here?” from real context instead of guessing.

What ContextCake is, in one sentence

ContextCake stitches your separate knowledge graphs — personal, team, company — into one OKF graph your agent can read, returning a primary answer and being honest about contradictions: which layers disagree, and when each was last updated.

Reading order

  1. overview/what-is-contextcake.md — the idea and the problem it solves
  2. overview/mental-model.md — the layer cake in one picture
  3. architecture/layers-and-precedence.md — how higher layers win, per section
  4. architecture/okf-format.md — the file shape everything resolves into
  5. getting-started/installation.md — get the engine running
  6. getting-started/writing-a-layer.md — author your first concept
  7. getting-started/connect-an-ai-agent.md — point your agent at the resolved graph
  8. examples/ — concrete concepts, a layers.json, and a resolved output
  9. nuances/ — the sharp edges worth knowing before you rely on it

How to use it with your tool

See tool-guides/ for Claude Code, ChatGPT, Cursor, and Copilot. The short version: keep these files where your assistant can read them, and it will have the real architecture and conventions in context.

Use it for

When it earns its place.

Adopting ContextCake

Wiring ContextCake into a repo and wanting your agent to actually know how it works.

Onboarding a teammate

Someone new needs the architecture and conventions without reading the whole codebase.

Building on the engine

Extending sources, the resolver, or the MCP server, and needing the model precise.

Explaining it to an AI tool

ChatGPT, Cursor, or Copilot should answer ContextCake questions accurately, not from stale guesses.

What’s inside

What you get out of it.

Understand the architecture fast
Federated storage, the resolver, section merge, and provenance — explained for someone adopting it, not just skimming marketing.
Get an agent productive
Tool guides plus an MCP walkthrough so Claude, Cursor, or Copilot can use ContextCake in your repo from real context.
Copy real examples
A full OKF concept, a working layers.json, and a resolved read_file payload with surfaced conflicts.
Avoid the sharp edges
The nuances that bite: precedence and recency, the manifest trust boundary, conflicts-not-hidden, the dependency-free rule.

Early access

Free while it’s in preview.

The full pack is free to read right now. Curated updates and more packs are on the way as paid add-ons — this pack stays free.

The pack

Freein preview

Read the whole thing, no signup.

ContextCake Context Pack

The full pack — overview, architecture, getting-started, use cases, examples, and nuances — free to read right now. Open the explorer above.

Read the full pack

Coming soon

Morepacks, later

Curated updates and additional profession packs.

Updates and more packs

When paid tiers open, this pack stays free. You’d only pay for ongoing curated updates and additional packs.

Coming soon

No checkout yet — the pack is free to read while it’s in preview. Paid updates and more packs are coming.

Works with your tools

Plain files first. Everything else is a bonus.

Plain files
Markdown you can open, read, and edit anywhere. This is the baseline — no tool required.
Claude Code
Add the ContextCake MCP server, or point Claude at the pack files.
ChatGPT
Upload the files as project or knowledge files, then reference them in prompts.
Cursor & Copilot
Keep the files in your repo so the assistant reads them as working context.

FAQ

Before you ask.

Is this just the ContextCake docs?

It overlaps, but it is packaged as portable context files an AI agent can pull into your project — not a website to browse. Same facts, agent-ready.

Do I need this to use ContextCake?

No. The engine is free and dependency-free. This pack gives your assistant the full, accurate context so it can help you wire ContextCake in faster.

Is it accurate to the current version?

Yes — it is distilled from the current design spec and docs, and it drops the superseded bits (no shadow-drift subsystem, no Group layer).

What becomes paid later?

The base pack stays free. Curated updates and additional packs are the future paid tiers.

The ContextCake context pack is made by ContextCake, the context layer that keeps team knowledge consistent across AI tools.

Learn about ContextCake