Think inside your AI world.
GitHub + Linear through Unl
Code can be green while scope is unfinished, or the reverse. A launch gate has to see both — and the two tools that hold each half can’t.
GitHub + Linear through Unl reads release readiness and delivered scope together against the launch gate you ratified, so “is it go?” covers code and plan in one verdict, with the unmet side named. The gate lives in Unl.
The criterion that binds them
You ratified one launch gate spanning both: the code conditions (checks passing, no open code-scanning alerts) and the plan conditions (scope complete, no open P0s), because a launch fails if either half does.
The two naked reads
GitHub returns PR and check status and alerts; Linear returns issues and milestones. Both accurate, each half-blind — neither can render the single go/no-go your gate is written as.
The one measured answer
Measured against your gate: code is ready — checks pass, no open alerts; plan is not — two P0s remain in Linear. Not go, and the blocking side is scope, not code. One gate over two reads produces one decision.
And back again
When you carve those two P0s into a fast-follow and narrow the launch scope, the revised gate is ratified in the same conversation — and the next read judges against the launch you now intend.
The answer comes back measured against what you already decided, and why.
A router can show GitHub and Linear together. It cannot decide a launch, because the gate — the conditions across both, and why they’re one gate — lives in neither repository nor board.
The lane is live and open to this tool today: one box, paste anything. If it speaks MCP, Unl can reach it. Readings arrive unprompted, the data beside the criterion; Unl is a courier, not a warehouse, and keeps only your keys and the frame.
Read further
Questions people ask
Can AI give a go/no-go across GitHub and Linear?
Yes, through Unl. You ratify one launch gate covering the code and plan conditions, with your reasoning, and GitHub and Linear are read together against it — the answer is go or not-go, with the blocking side named.
Why not just check each tool separately?
Separate checks leave you to combine them, and miss the case where each half looks fine alone but the gate isn’t met jointly. The single gate lives in Unl, so the read returns one verdict across both.
Does Unl push code or edit issues?
Unl reads through GitHub and Linear, and can write back on your explicit gesture — it never acts as a side effect of a read.
What if a required check never ran at all?
Then it has not passed, and a gate that treats absent as green is not a gate. A check that never ran and a check that passed look identical to anything counting only failures. Your launch gate spans code and plan conditions and needs both actually evaluated; the read distinguishes not-run from passed, because the first is a question and the second is an answer.
What this is
Think inside your AI world — you stay in command
Save the thoughts, decisions and targets worth keeping, each with its reasoning, carried into every AI session the moment they matter. A new unit of exchange between you and your AI: the Settled Why with standing that travels. Unprompted.
Your whole AI world. What you decided at the epicentre. It plugs into Claude, Claude Code, ChatGPT and Cursor as an MCP connector — quick to connect, in a couple of steps.
MCP native·Human settled·Model agnostic·Your data
Measured Context
Connect Unl to bring the right information into the moment.
Your sources, read against the criteria you set.
The full product, open. Free at launch.