Initialize an RLM semantic cache with guided configuration and bootstrap.
npx skills add https://github.com/richfrem/agent-plugins-skills --skill rlm-init
Please help me install this Agent Skill. Skill: rlm-init Source: https://github.com/richfrem/agent-plugins-skills/tree/main/plugins/rlm-factory/skills/rlm-init Command: npx skills add https://github.com/richfrem/agent-plugins-skills --skill rlm-init
Initialize an RLM semantic cache for a project, guiding setup from start to first distillation.
Run the rlm-init command to bootstrap a new semantic cache for your project.
High-intent search queries and answers about installing and using this skill.
To initialize a semantic cache, run the rlm-init command to trigger a guided interactive workflow that walks you through folder selection, extension configuration, manifest creation, and initial distillation.
Semantic cache initialization is the first-time setup process that seeds your project data into a cache profile. You need it when starting a new project or adding a new cache profile for different doc types.
Yes, you need Python 3.8 or higher to set up an RLM semantic cache. The initialization workflow requires this environment to configure extensions and perform the first distillation pass.
The best way to bootstrap a new cache profile is using the guided initialization workflow, which handles folder selection, extension configuration, and manifest creation before performing the initial distillation pass.
Yes, you can add new cache profiles to an existing setup by running the initialization workflow again, which guides you through configuring a new manifest and performing the first distillation for the new doc types.
Semantic cache initialization requires a manifest to define cache profiles and a first distillation pass to seed the cache with project data, ensuring the cache is populated and ready for automated workflow retrieval.
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