Runs coding agents as a graph: one agent implements, independent agents review, failures go to repair, and nothing ships until the checks pass. Works with Codex, Claude Code and Copilot.
This week was primarily documentation work, with a comprehensive refresh of the README, guides, and reference materials. The team restructured how Zeroshot's purpose and features are presented, added new comparison content, fixed community links, and made docs more accessible to both humans and AI…
Get this in your inbox every Monday →A deterministic 0–100 hygiene score — README, license, CI, tests, docs, and freshness.
Who ships this repo — author concentration and the bus factor across the last 300 mainline commits.
How welcoming this repo is to contributors — issue throughput, close time, responsiveness, and good-first-issue count.
What this project is built on — dependency count by ecosystem, the license mix, and anything worth a legal look before you adopt it.
Whether this project's CI can be trusted — pass rate, run times, flaky runs, and which workflow is the weak link.
Grounded in zeroshot's README, structure, and recent commits — answers won't invent code they haven't seen.
A Monday email with what shipped, in plain English — no account needed.
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docs: show per-step models and mark the custom topology as an example (#1190)
A floor, not a guess: counts only commits whose author, co-author trailer, or message explicitly credits an AI tool (Claude, Copilot, Cursor, aider, Codex…). Based on 30 mainline commits. Unattributed AI code isn't counted here — the full audit estimates that separately.
