PluginEvalv2.0.0

A skill marketplace administrator runs PluginEval as an automated quality gate before listing any new community-contributed skill. The vetting workflow combines ClawDefender security scanning with PluginEval quality scoring so only skills with no anti-patterns and a minimum badge score reach end users.

An engineering team integrates PluginEval into their CI pipeline to evaluate every pull request that modifies an existing skill. Scores are compared against a baseline so quality regressions, newly introduced anti-patterns, or security concerns block the merge automatically.

A skill author uses PluginEval to generate a combined security and quality report before publishing to ClawHub. The resulting badge (such as Gold or Platinum) is attached to the skill listing to build trust with prospective users and differentiate from unvetted alternatives.

A platform security team audits their private catalog of AI agent skills quarterly using PluginEval's combined vetting workflow. Reports feed a compliance dashboard that tracks quality trends, flagging any skill that drops below the organization's minimum security or quality threshold.

Maintainers of an open-source agent skill repository use PluginEval to review community submissions at scale. Contributors run vet-skill locally before opening a pull request, reducing reviewer burden and standardizing quality expectations across the project.

Offer PluginEval's basic security and quality checks for free while charging for advanced reporting, historical trend tracking, and private catalog dashboards. The core evaluation engine (plugineval-core) remains open, and premium features wrap it with team collaboration and analytics.

Sell a managed vetting gate to skill marketplaces and agent platforms, where PluginEval runs automatically on every submission and produces a verified badge. Platforms pay to outsource their trust and safety review pipeline, reducing their own engineering overhead.

Distribute PluginEval as a paid add-on for existing CI/CD and developer platforms, integrating quality scoring directly into pull request workflows. Revenue comes from seats or pipeline minutes consumed by automated evaluations.