Proof of Usefulness Report

agentguard: network egress firewall for AI agents

Analysis completed on 5/15/2026

+60.66
Proof of Usefulness Score
You're In Business

agentguard addresses a critical and timely vulnerability in AI agent development with a practical, zero-dependency allowlist approach, earning strong utility and market relevance scores. However, as a newly launched v0.1.0 project with minimal demonstrable user adoption or established audience reach beyond the author's previous open-source footprint, the current traction signals are extremely weak, placing the project squarely in the minimal traction category.

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Score Breakdown

Real World Utility+21.25
Audience Reach Impact+1.0
Technical Innovation+11.25
Evidence Of Traction+1.25
Market Timing Relevance+13.5
Functional Completeness+4.5
Subtotal+52.75
Usefulness Multiplierx1.15
Final Score+61

Project Details

Project URL
github.com/MukundaKatta/agentguard
Description
A tiny zero-dep JavaScript library that gives every AI agent tool a declarative allowlist of domains it can fetch from. If a tool tries to reach a domain you have not allowed, agentguard throws. Designed for teams running agents that browse the web or call third-party APIs and want a hard guardrail rather than a hope.
Audience Reach
Early stage. agentguard v0.1.0 published on npm on 2026-04-25. Author has shipped 30+ open-source libraries (npm/PyPI/crates.io) under @mukundakatta; distribution flywheel established.
Target Users
Teams running AI agents that fetch URLs or call APIs and need a hard guardrail rather than hoping the model never goes off-policy. Drop-in declarative allowlist; throws on first violation.
Technologies
Other, JavaScript, TypeScript, npm, Node, ESM, GitHub Actions
Traction Evidence
GitHub: https://github.com/MukundaKatta/agentguard (MIT). npm: https://www.npmjs.com/package/@mukundakatta/agentguard (v0.1.0 published 2026-04-25). Companion entries in same agent-stack ecosystem: agentmemory, agentsnap, agentcast, agentvet, agenttrace. Author maintains 30+ shipped open-source libraries under @mukundakatta.

Algorithm Insights

Market Position
Growing utility with room for optimization
User Engagement
Documented reach suggests active user community
Technical Stack
Modern tech stack aligned with sponsor technologies

Recommendations to Increase Usefulness Score

Document User Growth

Provide specific metrics on user acquisition and retention rates

Showcase Revenue Model

Detail sustainable monetization strategy and current revenue streams

Expand Evidence Base

Include testimonials, case studies, and third-party validation

Technical Roadmap

Share development milestones and feature completion timeline