rlat

Name: rlat
Availability: InStock
Author: tenfingerseddy

Orchestrate rlat CLI workflows for knowledge-model lifecycle management.

16|1|Updated Apr 9, 2026

Search Tags:#cli #workflow orchestration #drift #multi-hop #rlat #knowledge model

Ready to run

npx skills add https://github.com/tenfingerseddy/resonance-lattice --skill rlat

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: rlat
Source: https://github.com/tenfingerseddy/resonance-lattice/tree/main/.claude/skills/rlat
Command: npx skills add https://github.com/tenfingerseddy/resonance-lattice --skill rlat

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Orchestrate rlat CLI workflows on the user's behalf to manage knowledge-model lifecycles, reducing manual coordination and enabling consistent, auditable results.

Core Features & Use Cases

Orchestrates Init, Refresh, Search, Memory, Compare, Convert, Optimise, and Skill-context workflows from a single entry point.
Supports multi-hop research via the deep-research deferral for cross-file synthesis, and surfaces clear next steps.
Generates project primers and context when needed, while respecting storage modes and drift checks in local/remote setups.

Quick Start

Run rlat init-project to auto-detect sources and generate the primer and initial knowledge model.

Frequently Asked Questions about rlat

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I automate knowledge model lifecycle workflows from a single CLI entry point?▼

You can automate knowledge model lifecycle workflows by orchestrating init, refresh, search, memory, and optimise commands through a single CLI entry point, reducing manual coordination and ensuring consistent, auditable results.

What is multi-hop deep-research deferral for cross-file synthesis?▼

Multi-hop deep-research deferral is a workflow orchestration mechanism that delays cross-file synthesis to gather broader context, enabling comprehensive knowledge model searches and surfacing clear next steps for complex research tasks.

How do I initialize a project primer and generate an initial knowledge model?▼

Run the init-project command to auto-detect local and remote sources, which generates the project primer and builds the initial knowledge model while respecting storage modes and drift checks.

Can I manage local and remote knowledge-model storage with drift checks?▼

Yes, you can manage both local and remote knowledge-model storage by applying drift checks and safety guardrails, ensuring consistent state and auditable results across distributed setups.

What's the best way to surface past decisions and project context in workflow orchestration?▼

The best way to surface past decisions is by executing the memory workflow within the knowledge model, which retrieves historical context and generates project primers as needed for ongoing orchestration.

When should I not use automated workflow orchestration for knowledge models?▼

You should avoid automated workflow orchestration when your task requires bypassing safety guardrails or using tools outside the allowed Bash, Read, Write, Edit, Glob, and Grep scope, as the skill enforces strict operational constraints.