agents-cli
The CLI your coding agent uses to ship agents
170 followers
The CLI your coding agent uses to ship agents
170 followers
One command-line tool to scaffold, evaluate, and deploy AI agents on Google Cloud — built to be driven by your coding agent (e.g Antigravity, Claude Code, Codex). Scaffold a production-ready project, evaluate against a real signal, and ship to Agent Runtime, Cloud Run, or GKE or anywhere else!
Agent-first output with a human interactive mode is the right call, and rarer than it should be. The subtlety I keep hitting is partial failure. A single top-level 'deploy: ok' is easy for a model to over-trust, so we ended up emitting per-resource state, this bucket created, that Cloud Run revision rolled back, because 'ok' was hiding that one of three resources failed and the agent moved on. Does the agent-mode output break status out per step and resource, or is it one overall result the model has to interpret?
JustVibe
This sounds like an interesting approach to give coding agents the capability to handle the infrastructure portions for agents. Do you have plans to cover more types of infrastructure needed, like storage systems?
I'm also quite interested in learning about how you compare using agents-cli against other approaches like leveraging coding agent's own ability to discover and integrate with the infrastructure layers or using MCP servers. Or if you see them complementary.
Agents being the primary user of products is definitely the direction we are heading in. Curious to know how you do evals on the CLI? How do you validate if its suitable to be used by agents or run into the same confusion they might have had before?
Agent Starter Pack
@margharitha great question! we run specific simulations to check how agents cli performs on real scenarios with coding agents!
Treating evals and deploy as first-class commands is the part that matters. A demo agent is easy; a shippable agent needs a repeatable failure loop, logs someone can read, and a human checkpoint before it touches production. That makes the CLI feel more like release engineering than scaffolding.
Agent Starter Pack
@krekeltronics Exactly the mental model we are going for!
The "agent-first output, human-friendly only in interactive mode" philosophy is the detail that makes this click for me, @elia_secchi — I spend a lot of time on agent reliability, and the number of loops that break because a tool emits prose an agent misreads as success is higher than anyone admits.
Loved your reply to Tyler too: wiring the secret reference but making a human add the actual secret is exactly the right seam to keep a coding agent from minting prod creds. Nice work 👌
Agent Starter Pack
@akbar_b thanks a lot!
the eval run step is the part that's usually missing from these agent-scaffolding tools. everyone ships the "build me an agent in an afternoon" demo but scoring it against a dataset before deploy is what actually tells you if it's ready, not just that it compiles and responds to a prompt
Agent Starter Pack
@omri_ben_shoham1 yeah eval is super important to ship with confidence!
makes sense, good luck with the launch
Since agents-cli is designed to be driven autonomously by coding agents, what mechanisms exist to prevent 'configuration drift' or accidental over-provisioning of cloud resources if the coding agent interprets a prompt too broadly during the scaffolding or deployment phases?