Convert Markdown documentation into HADS-compliant [SPEC], [NOTE], and [BUG] blocks.
npx skills add https://github.com/haxlys/skills --skill hads-haxlys
Please help me install this Agent Skill. Skill: hads Source: https://github.com/haxlys/skills/tree/main/vendored/wshobson-agents/plugins/documentation-standards/skills/hads Command: npx skills add https://github.com/haxlys/skills --skill hads-haxlys
HADS enables writers and AI systems to exchange technical documentation by separating authoritative facts ([SPEC]), human context ([NOTE]), and verified issues ([BUG]), improving both human readability and machine interpretability.
Convert a sample document to HADS by replacing factual statements with [SPEC] blocks, moving narrative to [NOTE], and surfacing known issues as [BUG].
High-intent search queries and answers about installing and using this skill.
Converting Markdown into AI-readable blocks involves separating authoritative facts, human context, and verified issues into structured [SPEC], [NOTE], and [BUG] formats. This standardization ensures reliable machine interpretation and safer agent interactions.
The best way to structure technical docs for AI-assisted review is enforcing a standardized manifest with version banners and bolded blocks. Separating factual specifications from narrative notes improves both human readability and machine processing reliability.
AI agents struggle to parse standard Markdown because unstructured text mixes facts with context, reducing reliability. Applying a structured AI manifest with designated [SPEC], [NOTE], and [BUG] blocks separates authoritative data from narrative for safe consumption.
Yes, you can validate existing Markdown docs for AI-safe consumption by enforcing structural rules like version banners and bolded blocks. This process checks and standardizes documentation workflows to ensure reliable AI processing.
You need to separate facts, context, and issues when migrating docs for AI-assisted review or enabling safer agent interactions. Structuring content into [SPEC], [NOTE], and [BUG] blocks maintains audit trails and improves machine interpretability.
Unstructured Markdown limits AI agent reliability by blending factual statements with narrative context. Separating content into standardized [SPEC], [NOTE], and [BUG] blocks overcomes this constraint, ensuring accurate data extraction and safer processing.
PriyanshKuniyalValidate and convert technical documentation to the Human-AI Document Standard.
ArogyaReddyConvert Markdown documentation into HADS format with SPEC, NOTE, and BUG blocks.
anevjesAutomate documentation updates, audits, and standard enforcement across markdown files.
gaos6eAutomates creating, reading, editing, and formatting Word (.docx) files using Python scripts and supporting tools like defusedxml and lxml for parsing, modifying, reassembling them; extracts content and reorganizes documents with headings, tables, images, tracked changes, and comments.
