functional-area-resolver

Compress oversized LLM routing files into functional-area dispatchers preserving sub-skill reachability.

5|1|Updated Apr 15, 2026
One-click install
npx skills add https://github.com/GYF0311/lorekit --skill functional-area-resolver-gyf0311
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: functional-area-resolver
Source: https://github.com/GYF0311/lorekit/tree/main/brain/skills/functional-area-resolver
Command: npx skills add https://github.com/GYF0311/lorekit --skill functional-area-resolver-gyf0311

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It solves the context-budget blowup caused by large routing files (RESOLVER.md / AGENTS.md) that grow to hundreds of skill-per-row entries and waste prompt tokens on pipe-table routing.

Core Features & Use Cases

  • Functional-area dispatchers: Replaces many granular routing rows with one dispatcher entry per functional area, using a "(dispatcher for: ...)" clause so an LLM can still reach the correct sub-skill.
  • Routing correctness guardrails: Enforces preconditions (only compress when the file is large enough and the working tree is clean unless forced) and requires structural verification plus an LLM A/B harness check before committing edits.
  • Operational workflow for big resolvers: Guides you through choosing which routing file(s) to compress, crafting area trigger phrases, keeping always-on entries separate, and maintaining the internal dispatcher skill routing.

Quick Start

Tell your AI: compress my AGENTS.md (or RESOLVER.md) using functional-area dispatchers and verify routing accuracy with gbrain before committing the change.

Frequently Asked Questions about functional-area-resolver

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

FAQPage Schema
How do I compress oversized LLM routing files to save prompt tokens?▼

To compress oversized LLM routing files, convert per-skill routing rows in RESOLVER.md or AGENTS.md into functional-area dispatchers. This replaces many granular entries with one dispatcher per area, preserving sub-skill reachability while shrinking the context budget.

What is a functional-area dispatcher in skill routing?▼

A functional-area dispatcher is a single routing entry that replaces many granular skill-per-row entries in a large routing file. It uses a "(dispatcher for: ...)" clause so an LLM can still reach the correct sub-skill under limited context budgets.

When do I need to compress an AGENTS.md or RESOLVER.md routing table?▼

You need to compress an AGENTS.md or RESOLVER.md routing table when the file exceeds approximately 12KB and begins wasting prompt tokens on pipe-table routing. This context-budget blowup occurs when hundreds of skill-per-row entries grow too large.

How do I verify routing accuracy after compressing an LLM routing file?▼

To verify routing accuracy after compressing an LLM routing file, run structural routing evaluation followed by an LLM harness A/B test on the edited file. This ensures the functional-area dispatchers preserve sub-skill reachability before committing changes.

What are the preconditions for compressing a large routing file?▼

Preconditions for compressing a large routing file require the file to be sufficiently large (over ~12KB) and the working tree to be clean unless explicitly forced. Gatekeeping these preconditions ensures safe functional-area dispatcher conversion.

Does functional-area dispatcher routing work with always-on LLM workflow entries?▼

Yes, functional-area dispatcher routing works with always-on LLM workflow entries by keeping them separate from the compressed dispatcher entries. This maintains their immediate availability while still shrinking the overall routing table footprint.