Define browser navigation allowlists and configure screenshot and DOM evidence capture.
npx skills add https://github.com/AesopScott/mojo --skill navigation-policy
Please help me install this Agent Skill. Skill: navigation-policy Source: https://github.com/AesopScott/mojo/tree/main/harnesses/skills/navigation-policy Command: npx skills add https://github.com/AesopScott/mojo --skill navigation-policy
This Skill provides a structured framework for managing browser-based automation, ensuring that visual proof collection and navigation remain within safe, defined boundaries.
Use the navigation-policy skill to define the allowed navigation paths and evidence capture requirements for the current browser automation task.
High-intent search queries and answers about installing and using this skill.
To restrict browser automation, define explicit allowlists for navigation paths to prevent unauthorized access. This capability control confines automated agents to specific subdomains and ensures only relevant UI elements are captured.
Deterministic visual proof collection is the structured capture of screenshots and DOM evidence during automated browser workflows. It applies capability boundaries to ensure safe execution and produces consistent visual regression testing outputs.
Yes, you can configure specific connectors for capturing screenshots and DOM evidence. The framework manages evidence collection strategies to ensure that automated capture harnesses only collect approved visual proof.
You prevent accidental sensitive data collection by applying navigation policies that restrict agents to allowed paths. Defining these explicit boundaries ensures that automated visual regression testing only captures relevant UI elements.
The best way to manage audit logging is implementing a structured navigation policy that enforces capability boundaries. This provides deterministic proof collection and satisfies compliance requirements for safe browser execution.
You should not use navigation allowlists when a browser automation task requires open-ended exploration across unrestricted domains. The framework is designed for controlled capability boundaries and deterministic visual proof collection, limiting free-form scraping.
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