Generate Elasticsearch data artifacts from a demo script and discovery profile.
npx skills add https://github.com/ajmeyers42/loom --skill weave-model
Please help me install this Agent Skill. Skill: weave-model Source: https://github.com/ajmeyers42/loom/tree/main/skills/weave-model Command: npx skills add https://github.com/ajmeyers42/loom --skill weave-model
This Skill reads a demo script and discovery profile to generate all Elasticsearch data artifacts required to build a fully deployable Elastic demo, including index mappings, data stream templates, component templates, ILM policies, ingest pipelines, enrich policies, and sample data specifications. It produces a master build manifest and individual artifact files in the correct build order.
Supply a demo script and discovery JSON; weave-model will generate mappings, templates, pipelines, and a master data-model manifest in the correct build order.
High-intent search queries and answers about installing and using this skill.
To generate Elasticsearch index mappings and ingest pipelines from a discovery profile, supply the profile and a demo script to produce a complete data model. This process outputs component templates, ILM policies, and enrich policies ready for deployment.
Building a deployable Elasticsearch demo environment requires index mappings, data stream templates, component templates, ILM policies, ingest pipelines, and enrich policies. A master build manifest organizes these artifacts in the correct build sequence for bootstrapping.
Yes, you can use semantic_text with ELSER endpoints in Elasticsearch data models. The artifact generation process validates prerequisite ELSER endpoints to ensure Elasticsearch-native configurations align correctly when semantic_text is applicable.
Elasticsearch data model generation requires a baseline version of 9.4 or higher. The generation process applies baseline version checks to ensure compatibility and supports Vulcan outputs when present to accelerate artifact creation.
To create a master build manifest for Elasticsearch data artifacts, input a demo script and discovery JSON. The process emits machine-readable data-model JSON and human-readable Markdown, detailing mappings and pipelines in the correct build order.
The best way to bootstrap Elasticsearch data streams and component templates is by using a discovery profile and demo script to auto-generate the required artifacts. This approach ensures all configurations align with Elasticsearch-native settings and ELSER where applicable.
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