# IDEA-015: Package Screening Agent

**Date:** 2026-03-04
**Source:** user
**Status:** raw

## Idea

A dedicated agent that performs full due diligence on any tool, library, or package before it gets adopted into iEvo or recommended in a proposal. Given a package name or URL, it runs a structured screening across all available signals: GitHub health, community sentiment, release cadence, integration count, maturity level, and fit for the target task.

Screening dimensions:
- **GitHub vitals**: stars, forks, open/closed issues ratio, PR velocity, last commit, contributors count, release frequency
- **Maturity signals**: age of project, semver stability (v0.x vs v1+), breaking changes history, deprecation notices
- **Community health**: Reddit discussions (r/MachineLearning, r/LocalLLaMA, r/Python, etc.), HN threads, Discord/Slack activity, Stack Overflow questions
- **Integration count**: how many other packages depend on it, listed integrations, ecosystem breadth
- **Downloads / adoption**: PyPI weekly downloads, npm downloads, Docker pulls — actual usage numbers
- **Maintenance signals**: response time on issues, bus factor (single maintainer vs org), corporate backing
- **Feature fit**: does it actually solve the target task? what are known limitations?
- **License**: compatible with iEvo's license?
- **Security**: known CVEs, audit status, dependency chain health (via deps.dev or similar)
- **Alternatives**: what else exists, how does it compare

Output: a structured screening report with a final verdict — Adopt / Evaluate / Avoid — and reasoning.

## Why

Research agents currently just find and describe packages. There's no systematic gatekeeping before a package enters a proposal or gets added as a dependency. A screening agent prevents adopting packages that look good on the surface but are abandoned, single-maintainer, poorly maintained, or a bad fit — saving time and technical debt.
