BUILTLive
ROUTR
Small router skills that send an AI coding agent to the right workflow before it reads anything.
Snapshot
- My role
- Author and maintainer
- Timeframe
- July 2026 – present
- Status
- Live
- Team size
- 1
The problem
An agent with dozens of installed skills tends to pick the wrong one and read whole files to find out, burning its context window. ROUTR puts a thin layer in front: 28 routr-* router skills with explicit “use when / not for” descriptions, so routing is decided from the slash-menu text and only the one full playbook needed gets loaded. Requests that span several workflows get a route plan of at most three steps, with one router active at a time.
How the project ran
I owned
- Designed the router format: a tight “Use when / Not for” description, an exit condition and a handoff
- Wrote the 28 router skills and the routes.json file that defines handoffs, companions and chains
- Built the skill validator that runs in CI on every change
- Wrote the 153-prompt single-router eval set plus multi-route and held-out chain prompts, and ran the blind evaluations
Constraints
- Routing has to work from short descriptions alone — the agent should not load a playbook to decide whether it needs it
- Real requests span several workflows, but two routers active at once would contradict each other
- Child skills may not be installed, so every router needs a fallback
Outcome
- MIT-licensed and installable with one command
- Blind runs with a model that saw only the prompt file and menu reached 99.3% and 97.4% router accuracy on the 153-prompt set, as reported in the README; the method is published so the numbers can be reproduced
- Route plans capped at three steps, with one active router and at most one companion checklist per step
- Missing child skills fall back to built-in routr-depth-* skills instead of failing
Learned
- Description text is the routing interface — the “not for” boundaries matter as much as the “use when” ones
- Chain prompts written before the composition rules, and never used for tuning, give a more honest measure than a tuned set
Built with
- Python
- PowerShell
- Shell
- GitHub Actions
Evidence
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