Context engineering makes or breaks your agents
Models have no persistent memory across sessions.
Same clarifications, same architecture, every time.
Redundant context burns the attention budget.
Decisions and intent never persist for the model.
As tokens grow, recall drops — context rot.
Automated context management clutters the context. Curation needs a human.
Further reading: Anthropic on effective context engineering · Chroma on context rot
Meet Context Layer — curated domain intelligence for AI agents
Simple
No magic, just folders and symlinks.
Reusable
Reuse the context between projects.
Clean
Doesn't pollute your repo. Context is stored separately from domain code.
Agent-agnostic
Cursor, Claude, future agents.
Persistent
Store the context on your file system or in a dedicated GitHub repository.
Human-in-the-Loop
You curate your domain context.
Built for engineers who treat context as a first-class resource
AI-first developers Independent builders using LLMs daily Engineers automating repeatable work Developers running multi-agent workflows Founders optimizing AI development cost
How it works
This is how your project directory looks like with the context layer.
my-project/
├── README.md
├── ... # your project files
└── .ctxlayer/ # symlink to ~/.agents/ctxlayer/
└── my-domain/
├── config.yaml
├── task-1/
│ ├── docs/
│ │ ├── 01-initial-research.md
│ │ └── 02-implementation-notes.md
│ └── data/
│ └── sample-data.json
└── task-2/
├── docs/
└── data/
- The context layer is a directory structure on your machine.
- Reference domain intelligence across domains via symlinks.
- The context layer is not stored in the project repo, but can be persisted in a dedicated GitHub repo.
- Reference the context from agent prompts by saying "in the context layer".
Quick start
- Install the ctx CLI and agent skill.
- From your project directory, run
ctx new— Create a new task to hold the context for the task you are about to do. Initializes the context layer for your domain if it was not yet initialized. - Add docs/data — Add your documentation and reference material to the task's
docs/anddata/folders. - Ask agent — From your prompts, say "in the context layer, …". This keyword is understood by the agent and refers to the context layer directory of the active task.