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AI Riders
Context is everything. But not everything belongs in context.
Your AI instructions are scattered across personal preferences, repository files, tool configs, and chat history — different owners, different scopes, no expiry. A Rider is the durable half: what every agent should assume about how you work, which technologies are policy rather than habit, and what an agent may do without asking. Compile it once, export it for Claude Code, Cursor, Copilot, and AGENTS.md.
Local-only. Nothing is sent anywhere.
Everything here runs in your browser. No account, no upload, no network request. Your draft is kept only in this tab unless you press Save draft to this browser, and anything that looks like a credential is redacted before it is stored or shown.
- Policy domains
- 14
- Technology decisions
- 0/21
- Actions governed
- 12
- Sources imported
- 0
Areas a complete rider covers
Capabilities with a chosen implementation
All at safe defaults
Instruction files you have pasted in
Start here
The interview is the fastest route to a first rider. Everything else refines it.
Guided interview — next releaseThe six areas
Audit
Next releasePaste what your agents load today and see what each rule actually is.
Optimize
Next releaseTechnology decisions and the actions an agent may take on your behalf.
Context Packs
Next releaseWhich policy loads for which task, and why it activated.
Policy Drift
Next releaseWhere instructions, packages, and tools stop matching the policy.
Reports
Next releaseExportable artifacts, context exposure, and validation coverage.
Founding waitlist
Keep this analysis. The workspace saves it.
The paid workspace adds saved reports and score history, API and CLI access, and team governance — opening to the founding waitlist first, at founding pricing locked in before public launch. This tool stays free either way.