suggest-users

Rank GitHub collaborators as reviewers and assignees using CODEOWNERS and activity.

6|2|Updated Dec 19, 2025

Search Tags:#github #code-review #codeowners #assignees #workload-balancing #reviewer-suggestions #scoring-algorithm

Ready to run

npx skills add https://github.com/synaptiai/synapti-marketplace --skill suggest-users

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: suggest-users
Source: https://github.com/synaptiai/synapti-marketplace/tree/main/plugins/gh-workflow/skills/suggest-users
Command: npx skills add https://github.com/synaptiai/synapti-marketplace --skill suggest-users

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Manual selection of reviewers and assignees is slow, error-prone, and can overload active contributors; this skill automates candidate ranking so teams get the right people assigned quickly and fairly.

Core Features & Use Cases

CODEOWNERS matching: Prioritizes explicit owners declared in CODEOWNERS.
File-level expertise & activity: Uses recent commits and PR history to surface contributors familiar with changed files.
Workload balancing & fallbacks: Applies penalties for open reviews, uses extended lookback windows, and falls back to collaborators when ownership or API data is missing.
Use Case: When opening a PR, produce a ranked list of reviewers with reasons (ownership, recent commits, review load) so the creator can add the best reviewers with one action.

Quick Start

Suggest reviewers for pull request #123 by analyzing CODEOWNERS, changed files, recent PR activity, and current open review load.

Frequently Asked Questions about suggest-users

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I automatically suggest reviewers for a GitHub pull request based on code ownership?▼

To suggest reviewers for a GitHub pull request, the skill parses your CODEOWNERS file and matches changed files to rank collaborators based on file-level expertise, recent activity, and workload balancing.

How does workload balancing factor into assigning pull requests on GitHub?▼

Workload balancing for pull request assignment applies penalties to collaborators based on their current open review load, preventing active contributors from being overloaded while ranking available candidates.

What happens when the GitHub API is unavailable or CODEOWNERS data is missing during issue assignment?▼

When GitHub API data or ownership rules are missing during issue assignment, the skill falls back to querying local git logs, applies extended lookback windows, and ranks all available collaborators.

Can I use local git logs to find file-level expertise for reviewer suggestions?▼

You can use local git logs to find file-level expertise for reviewer suggestions, as the skill queries commit history to surface contributors familiar with changed files when GitHub API data is unavailable.

How do I rank collaborators for reviewer substitution on GitHub?▼

To rank collaborators for reviewer substitution, the skill computes configurable weighted scores using recent PR history, file-level commits, and current open review load to identify the best alternative reviewers.

Does this reviewer suggestion tool work for both issues and pull requests?▼

The reviewer suggestion tool works for both issues and pull requests, ranking collaborators using CODEOWNERS matching, file-level expertise, and recent activity across PR creation and issue assignment scenarios.