Problem
My agent loses the plot on a big codebase
Your agent loses the plot because it tries to read a big codebase one file at a time, burning its context window before it understands anything. CatWrangler hands it a briefing instead: describe the intent, get the relevant decisions, structure, and where to work.
On a large or legacy codebase, an agent that crawls file by file runs out of working memory before it understands the project. CatWrangler flips that around — the agent arrives with context instead of spending its budget assembling it.
Briefing, not crawling
When CatWrangler first connects to your repo, it reads the existing code and docs — so it works on the codebase you already have, large or legacy, not a fresh start.
From then on, an agent doesn't grep its way through the tree to orient itself. It describes what it's trying to do and gets back a pre-digested briefing scoped to that intent.
- What the project is and how it's organized
- The decisions that govern the relevant area — and what they depend on
- Exactly where the work should happen
- The code that already exists, so the agent extends it instead of rediscovering it
Why the plot stays intact
The context window is finite. An agent that spends it reading irrelevant files has nothing left for the actual work, and that's when it drifts. Finding by intent means the agent loads only what matters and keeps its budget for thinking.
Because the reasoning behind the code travels with the code, the agent starts a task already knowing why things are the way they are — not guessing from what it happened to read first.
“Without that gate I might have kept grepping forever and never learned the param exists.”
Related questions
Does this work on a large or legacy codebase, or only new projects?
Both. On first connect, CatWrangler reads your existing code and docs and builds the picture from what's already there — so a big, established repo is exactly the case it's built for, not an obstacle.
How does a briefing save the context window?
Instead of reading file after file to figure out what's relevant, the agent describes its intent and gets back just the project structure, the governing decisions, and where to work. It loads what matters and keeps the rest of its budget for the task.
Keep reading
Vibe-Engineering
Many agents. One codebase. Zero collisions.
Point your agents at CatWrangler and build — the discipline runs underneath.