Automate adding #(doc) tags to Malloy model sources and fields.
npx skills add https://github.com/malloydata/publisher --skill malloy-document
Please help me install this Agent Skill. Skill: malloy-document Source: https://github.com/malloydata/publisher/tree/main/skills/malloy-document Command: npx skills add https://github.com/malloydata/publisher --skill malloy-document
Malloy models often lack documentation for sources and fields, making it difficult to understand and use the models effectively.
Run the 'malloy-document' skill to add documentation to your Malloy model fields and sources.
High-intent search queries and answers about installing and using this skill.
You can document Malloy models by running an automated annotation process that generates human-readable descriptions. This adds #(doc) tags directly to fields and sources, making the models easier to understand and search.
The best way to improve discoverability is by adding clear, concise documentation to sources and fields. Annotating Malloy models with #(doc) tags helps both analysts and AI agents understand the data structure and usage effectively.
Adding #(doc) tags enhances model discoverability by embedding human-readable descriptions directly into the data structure. This makes Malloy model contents more easily understandable for end-users and AI agents during search.
Yes, you can automate the annotation of Malloy models with human-readable descriptions. This process automatically generates #(doc) tags for sources and fields, enhancing the documentation capabilities and understandability of your models.
Malloy models lack understandability for AI agents when they lack documentation for sources and fields. Adding clear descriptions through #(doc) tags makes the data structure and usage more easily understandable for automated agents.
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