implementation

Initialize AutoGen Team

Inspect the original prompt language first, then copy or adapt it once you know how it fits your workflow.

Linked challenge: Automating Open Source Maintainer Support with AutoGen Multi-Agent Teams

Format

Text-first

Lines

Sections

Linked challenge

Automating Open Source Maintainer Support with AutoGen Multi-Agent Teams

Prompt source

Original prompt text with formatting preserved for inspection.

1 lines

1 sections

No variables

0 checklist items

Import autogen and setup a manager with three roles: Triage, Analyzer, and Communicator. Define a groupchat object to handle the logic for PR evaluation.

Adaptation plan

Keep the source stable, then change the prompt in a predictable order so the next run is easier to evaluate.

Keep stable

Hold the task contract and output shape stable so generated implementations remain comparable.

Tune next

Update libraries, interfaces, and environment assumptions to match the stack you actually run.

Verify after

Test failure handling, edge cases, and any code paths that depend on hidden context or secrets.

Prompt diagnostics

Variables

Lists

Code blocks

Purpose

implementation

This prompt is mostly narrative and instruction-driven, so adapt examples and output constraints before you rewrite the structure.

Linked challenge

Automating Open Source Maintainer Support with AutoGen Multi-Agent Teams

Address the challenge of low-quality AI-generated pull requests by creating a multi-agent system using AutoGen. This system will act as a triage layer that evaluates contributions, checks for style guide compliance, and provides automated feedback to developers. By implementing a gatekeeper agent, an analyst agent, and a communicator agent, you can effectively filter noise while maintaining community standards. The project focuses on automated quality assurance and human-in-the-loop workflows to protect project integrity.

Open challenge

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