Extract OML vocabulary and instance semantics from repository source files.
npx skills add https://github.com/dwagmuse/dw-oml-3 --skill oml-text
Please help me install this Agent Skill. Skill: oml-text Source: https://github.com/dwagmuse/dw-oml-3/tree/main/.claude/skills/oml-text Command: npx skills add https://github.com/dwagmuse/dw-oml-3 --skill oml-text
The oml-text Skill helps you produce accurate answers by inspecting and reasoning over the actual OML source text (files, IRIs, declarations, and layout) instead of relying only on higher-level model views that may be incomplete or unavailable.
src/model/oml/) and avoid built artifacts.extends, uses, and containment relationships carefully.oml-mcp when the workflow becomes primarily model navigation/validation/structured querying.Use the oml-text skill to answer a question by reading the smallest relevant OML file(s) and extracting the exact declarations and semantics from the source text.
High-intent search queries and answers about installing and using this skill.
To extract OML ontology vocabulary and instance semantics from repository files, read the smallest relevant source files under likely locations like src/model/oml/ and pull exact declarations, avoiding built artifacts. This preserves accurate syntax-level details such as aliases, annotations, and comments.
Analyzing OML source text when OML MCP is unavailable requires inspecting actual repository files, IRIs, and declarations directly. This approach ensures accurate answers by relying on syntax-level inspection and cross-file comparison rather than higher-level model views that may be incomplete.
To preserve semantics when comparing OML declarations across multiple files, use targeted reads to cross-check IRIs and distinguish vocabulary definitions from description instances. Treat extends, uses, and containment relationships carefully to synthesize accurate assumptions.
You should escalate from source-text analysis to OML MCP when the workflow becomes primarily model navigation, validation, or structured querying. Source-text driven answers are best for syntax-accurate authoring details, while MCP handles higher-level model views.
Yes, source-first OML authoring analysis supports inspecting annotations, comments, and aliases by extracting precise ontology vocabulary and instance semantics directly from repository files. This ensures syntax-accurate details are preserved during repository-structured navigation.
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