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Monitor tasks and open pull requests with long-running agents

A commenter runs a persistent script that watches tasks and uses Cursor to open pull requests, building a documentation summarizer and a data pipeline.

Time saved
Not reported
Setup time
Not reported
Running cost
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Cost range
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Use case overview

A commenter runs a persistent script that watches tasks and uses Cursor to open pull requests, building a documentation summarizer and a data pipeline.

Reported experience

  1. What they did

    In a comment, the team said they run a Claude Code server on a VPS using the Caliber AI setup repo. That setup generates MCP configs and agent skills for their codebase and Cursor, they sync the environment with one command, and then a persistent script watches tasks and has Cursor open pull requests; the examples they named were a documentation summarizer and a data pipeline.

  2. How it went

    They said this workflow was used to build a few internal tools, specifically those two examples. The comment gives no metrics, timeline, or detail on review, so the results are described only at a high level.

  3. Worth knowing

    The main implementation catch they mention is infrastructure: a VPS-hosted Claude Code server, generated MCP configs and skills, and a one-command environment sync.

Example prompts

Try with Cursor
In my repo [repo name], read the open tasks in [issue tracker or task file] and for the one I pick, make the code change on a new branch, run the tests, and open a pull request with a clear description. Start by listing the tasks you could handle and wait for my choice, and do not merge anything. Finish when the pull request is open and tests pass.
Software & DevOps

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