Free tool
Agent Readiness Scorecard
Answer 10 quick questions. See which of your workflows are ready for an always-on agent like a Dot — and which need more structure first.
Last verified: September 30, 2026 · Reviewed by AstraDot editorial desk
Always-on agents such as OpenAI Dots work best on work that is repetitive, has a clear definition of done, can reach the right tools, and can be reviewed before it matters. Score your own workflow below.
—
Dimension breakdown
Get the readiness playbook
Enter your email and we'll send a short playbook for your score band — plus early access to the agent-ops toolkit we're building (and you can leave the waitlist anytime). We are an independent guide, not OpenAI.
This is a directional self-assessment from an independent guide, not professional advice and not a prediction of results. See our disclaimer.
How scoring works
- Volume — is the work repeated enough to be worth automating?
- Clarity — can you describe and check what "good" looks like?
- Access — can the agent reach the tools and data through apps or APIs?
- Review — can a person approve output before it has consequences?
- Risk — the more sensitive or consequential, the lower the readiness (scored in reverse).
New to Dots? Read what OpenAI Dots are first, then how they stay in control.