You have an evening for your projects. Someone has opened a pull request. Someone else asked a question. The useful starting point is knowing who is waiting and what you can do for them.
That is the question behind Standup. Give it a GitHub handle and it reads public repository activity, then prepares a short set of recommended next actions with the evidence it used.
We built it for the Agents for Humans Hackathon using the Strands Agents SDK. The example is small enough to inspect and familiar enough to recognise in other kinds of work.
A brief earns its place when you can act on it and check why.
The ordering rule is the product
Standup puts a person waiting for help ahead of a task that only costs the maintainer time. It distinguishes automated activity from human requests. A quiet account can receive one useful recommendation instead of a padded list.
Those choices define what the brief values. Asking a model to summarise everything would leave the most important product decision unresolved: what should come first?
The repository includes a recorded run over public projects. Its recommendations identify reviews and replies, cite the relevant issues or pull requests and give rough effort estimates. The accompanying audit lists what was read. That is a historical example of output, not a claim about those projects' current needs. The estimates are the model's suggestions, not measured completion times.
Keep the reader able to disagree
A recommendation is more useful when its reasoning is available. You may know a contributor is already speaking to someone, or that a change depends on work elsewhere. The brief should give you enough detail to correct it.
Standup's analysis tools read GitHub; they do not merge a pull request or send a reply. Its optional GitHub Action has a separate publishing step that can write the brief into an issue. Keeping that distinction visible helps an operator understand which part observes and which part writes.
From a brief to an operating loop
The Bridge applies a related idea to our fleet: collect evidence, identify the next useful decision and retain a record of the work. Its outcome evaluator can also say there is too little evidence to judge a result.
These examples suggest a practical starting point for a client workflow. Pick a recurring question that already has an owner: which support cases need intervention, which handovers are incomplete, or which delivery exceptions deserve attention? These are possible applications, not claimed deployments.
Then agree the ordering rule with that owner. Read the permitted sources. Show the supporting record beside each recommendation. Give people a way to correct the conclusion before adding authority to act on it.
What to watch: generating a summary is increasingly easy. A useful service still needs a clear definition of what deserves attention. Compare one proposed brief with the decisions your team actually makes; disagreements show where the context or ordering needs work.
Send Standup to someone returning to their open-source projects. If your team assembles a similar picture across business tools, tell us what the morning question is and where its answers live.