Generate technical documentation and Mermaid diagrams with YAML frontmatter-driven discovery.
npx skills add https://github.com/junevm/avtoolz --skill technical-docs-junevm
Please help me install this Agent Skill. Skill: technical-docs Source: https://github.com/junevm/avtoolz/tree/main/.agents/skills/technical-docs Command: npx skills add https://github.com/junevm/avtoolz --skill technical-docs-junevm
This Skill solves the problem of documentation drift by helping you write, audit, and visualize technical documentation directly alongside code changes.
Use the technical-docs skill to audit your latest changes and generate Mermaid ERD and sequence diagrams that match the current codebase.
High-intent search queries and answers about installing and using this skill.
Documentation-as-code practices keep technical documentation synchronized with code changes by running audit workflows that detect undocumented exports and outdated defaults via diffs. This approach treats docs as code, ensuring they remain accurate through CI-friendly structured checks.
Diagram-as-code generation drafts Mermaid flowcharts, ERDs, sequence diagrams, and gitGraph visuals directly from architecture or code context. This process translates existing structural data into visual representations without manual drawing.
Documentation coverage gap analysis identifies undocumented exports, feature gaps, and outdated defaults within software projects. You need this process when documentation drift occurs, ensuring technical docs accurately reflect the current codebase state.
YAML frontmatter-driven discovery supports documentation-as-code practices by providing structured metadata for automated retrieval. This enables CI-friendly structures to locate and process technical documentation, runbooks, and style guides deterministically.
AI-assisted drafting applies to ADR drafting, runbooks, and style guides while enforcing human verification for correctness. This workflow includes guardrails to validate link and snippet validity, ensuring generated technical documentation remains accurate.
Structuring technical documentation as code with CI-friendly formats enables automated audit workflows and documentation coverage gap analysis. This approach supports deterministic review steps, YAML frontmatter discovery, and consistent style guide enforcement.
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