Round 1 Winners!
Proof of Usefulness Report

HOL Guard

Analysis completed on 7/26/2026

+301.76
Proof of Usefulness Score
Certified Problem Solver

HOL Guard addresses a highly relevant problem by providing an open-source security layer for AI agents. With over 412K lifetime downloads, 132K monthly downloads, and solid integration standards (MCP SDK), it demonstrates strong early traction and excellent market timing. While it has not yet reached the enterprise scale of the calibration baseline, its technical utility and rapid adoption warrant a solid score in the comparable range.

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Score Breakdown

Real World Utility+85.0
Audience Reach Impact+36.0
Technical Innovation+48.0
Evidence Of Traction+90.0
Market Timing Relevance+54.0
Functional Completeness+15.0
Subtotal+328
Usefulness Multiplierx0.92
Final Score+302

Project Details

Project URL
Description
HOL Guard is the firewall for AI agents. It sits between agents and your systems, blocking high-risk actions before they happen like deleting production data to exposing secrets. Built by HOL, it’s free, open source, and already has 400K+ downloads. HOL Guard is useful for developers, vibe coders, marketers and anyone using tools like ChatGPT and Claude Code.
Audience Reach
HOL Guard and its CI companion, Plugin Scanner, have surpassed 412K combined lifetime downloads, including nearly 132K downloads in the last 30 days. The HOL Guard repository has 400+ GitHub stars and 1,100+ merged pull requests. The broader HOL open-source ecosystem spans 40 repositories, 834K+ lifetime package downloads, 3.5K+ GitHub stars, 1,900+ merged pull requests, 20+ published specifications, and partnerships with 30+ organizations. Plugin Scanner is also used by more than 100 open-source maintainers to review AI plugins, skills, MCP servers, and marketplace packages before release.
Target Users
HOL Guard is for anyone using AI agents that can interact with files, tools, packages, credentials, or external systems. Individual users gain a free, local security layer for agents such as Codex, Claude Code, Copilot CLI, Cursor, Gemini CLI, OpenCode, Hermes, OpenClaw, Pi, Kimi, Grok, and ZCode. Developers and open-source maintainers use Guard and Plugin Scanner to review commands, MCP servers, plugins, skills, hooks, configurations, and package installs. Engineering, security, and platform teams use it to introduce human approval, shared policy, audit evidence, and supply-chain controls as agents move into real workflows. The project is especially valuable to organizations that want the benefits of AI agents without granting autonomous software unchecked access to sensitive machines and systems.
Technologies
Other, Algolia, Python 3.10+, React, TypeScript, Vite, MCP SDK, cryptography, system keyrings, Cisco AI Defense open-source scanners, Docker/GHCR, GitHub Actions, PyPI, Playwright, pytest, and OpenSSF Scorecard. HOL Guard uses a Python runtime and policy engine with structured command parsing, typed risk signals, local encrypted state, agent-specific adapters, supply-chain analysis, approval workflows, and security receipts. Its local dashboard is built with React and TypeScript.
Traction Evidence
Open-source impact and current download data: https://hol.org/open-source Live product: https://hol.org/guard HOL Guard source, releases, issues, tests, and documentation: https://github.com/hashgraph-online/hol-guard HOL Guard package: https://pypi.org/project/hol-guard/ Plugin Scanner package: https://pypi.org/project/plugin-scanner/ Awesome Codex Plugins community: https://github.com/hashgraph-online/awesome-codex-plugins Published open standards: https://github.com/hiero-ledger/hiero-consensus-specifications

Algorithm Insights

Market Position
Strong market validation with clear user adoption patterns
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