Turn GitHub issues into draft pull requests with long-running agents
I really have no interest in this if it's going to use my plan's regular limits. Task: I really have no interest in this if it's going to use my plan's regular limits. I have less control over the context window, if its going off task. I used dots and enjoyed it because I could supplement my codex usage with read heavy long horizon tasks like reading gh issues and making pr's. These PR's were typically pretty bad but gave some starting point. I have much better real world output with the Claude Code style human in the loop approach to task solving.; tools: Dots, Codex, Claude Code. Human role: The original post does not say how a person stayed involved.; limitations: Prerequisites include access to Dots, Codex, and Claude Code. A key constraint is avoiding consumption of regular plan limits, which the author explicitly rejects. Context window control is limited when agents go off-task. Source reliability is secondary (user comment), and human approval is required before any changes are finalized..
Tools
Published on Agent Work Atlas:
Overview
I really have no interest in this if it's going to use my plan's regular limits.
Workflow
I really have no interest in this if it's going to use my plan's regular limits. I have less control over the context window, if its going off task. I used dots and enjoyed it because I could supplement my codex usage with read heavy long horizon tasks like reading gh issues and making pr's. These PR's were typically pretty bad but gave some starting point. I have much better real world output with the Claude Code style human in the loop approach to task solving.
Reported result
The source does not report measured outcomes or success metrics. It notes that Dots-generated PRs were 'typically pretty bad' but provided a starting point, while the human-in-the-loop approach yielded 'much better real world output.' No quantitative data on efficiency or quality improvement is available.
Human role
The original post does not say how a person stayed involved.
Limitations
Prerequisites include access to Dots, Codex, and Claude Code. A key constraint is avoiding consumption of regular plan limits, which the author explicitly rejects. Context window control is limited when agents go off-task. Source reliability is secondary (user comment), and human approval is required before any changes are finalized.
Try it
I want to test a workflow for converting GitHub issues into draft PRs without consuming my main plan limits. I have a list of open issues in [replaceable: repo URL] and access to Dots, Codex, and Claude Code. First, use Dots to read the issues and generate draft PRs as a starting point. Then, switch to Claude Code for a human-in-the-loop refinement process. Before sending any PRs or making changes, I must review the output. Start with one sample issue: [replaceable: issue number]. Show me the draft PR and the refined version. Do not publish anything until I confirm the quality is acceptable. If the draft is poor, note why and how the human-in-the-loop step improved it. Measure success by whether the final PR is mergeable and if the process stayed within separate quota limits.
Source reports are not independently verified. Publication date is the catalog publication date, not the original article date.