Diagnose codebase health and recommend GVM pipeline entry points.
npx skills add https://github.com/gerquinn1978/gvm --skill gvm-site-survey
Please help me install this Agent Skill. Skill: gvm-site-survey Source: https://github.com/gerquinn1978/gvm/tree/main/grounded-vibe-methodology/skills/gvm-site-survey Command: npx skills add https://github.com/gerquinn1978/gvm --skill gvm-site-survey
The gvm-site-survey skill provides a comprehensive diagnostic and health assessment of existing codebases, helping users understand their current state and guiding them towards the most suitable entry point in the GVM pipeline.
Run the gvm-site-survey skill to assess your codebase's health and architecture.
High-intent search queries and answers about installing and using this skill.
To assess codebase architecture for modernization, you conduct a diagnostic survey that scores coherence, modularity, and dependency health. This analysis identifies architectural patterns, boundaries, and data flow to determine the system's current state and guide remediation efforts.
A codebase diagnostic survey is a comprehensive health assessment of source code, configuration files, and version control history. You need it when starting work on an existing codebase to understand the system's architecture, identify areas of concern, and recommend next steps.
To select the right pipeline entry point, you run a diagnostic assessment that scores codebase health across multiple dimensions. Based on the diagnosis and nature of intended work, it recommends the appropriate starting phase, such as requirements, technical specification, or build.
You can map architectural boundaries and data flow by running an automated diagnostic assessment. It analyzes source code and configuration files to identify patterns, conventions, and structural boundaries within the existing system architecture.
The codebase assessment operates on source code, configuration files, and version control history to evaluate tech stack health. It selects tailored expert systems based on the diagnosis to guide remediation and modernization efforts across different stacks.
Automated codebase health assessments are limited to analyzing source code, configuration files, and version control history. They provide diagnostic scores and recommendations but do not execute remediation directly; they guide downstream pipeline phases instead.
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