AgentBase

What it does

Today, PR review means juggling tabs, hunting for context, and rubber-stamping because you're already three PRs behind. AgentBase fixes that — one calm workspace, author intent pinned to every diff, and a little green sapling named Sprig who actually read your PR. Reviewing stops feeling like a chore.

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  PR-Agent by CodiumAI2024 · ▲389

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  FlexReview2024 · ▲136

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  MoApr 2026 · ▲96

  Checks PRs against decisions your team approved in Slack

• IB
  I built a tool to assist AI agents to know when a PR is good to goJan 2026 · dsifry.github.io · ▲45

  I've been using Claude Code heavily, and kept hitting the same issue: the agent would push changes, respond to reviews, wait for CI... but never really know when it was done. It would poll CI in loops. Miss actionable comments buried among 15 CodeRabbit suggestions. Or declare victory while threads were still unresolved. The core problem: no deterministic way for an agent to know a PR is ready to merge. So I built gtg (Good To Go). One command, one answer: $ gtg 123 OK PR #123: READY CI: success (5/5 passed) Threads: 3/3 resolved It aggregates CI status, classifies review comments…

• SP
  Stage – Putting humans back in control of code reviewApr 2026 · stagereview.app · ▲130

  Hey HN! We're Charles and Dean, and we're building Stage: a code review tool that guides you through reading a PR step by step, instead of piecing together a giant diff. Here's a demo video: https://www.tella.tv/video/stage-demo-1pph. You can play around with some example PRs here: https://stagereview.app/explore. Teams are moving faster than ever with AI these days, but more and more engineers are merging changes that they don't really understand. The bottleneck isn't writing code anymore, it's reviewing it. We're two engineers who got frustrated with…

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• NW
  Needle: We Distilled Gemini Tool Calling into a 26M Model▲776

  Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…

  Life & fun · May 2026 · github.com

• FM
  Files.md – Open-source alternative to Obsidian▲730

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