By zpankz
Recursive context modularization, dependency analysis, and hyperedge bridge extraction
A production-ready Agent Skill that builds recursive dependency-aware modular architecture from raw context using an atom-of-thought pipeline, semantic graph analysis, adaptive decomposition, and cycle/bridge extraction.
This repository ships a standalone implementation for:
SKILL.md: skill contract (metadata + instructions) loaded by agent skill loaders.scripts/: orchestration engine and implementation.tests/: validation and regression tests.references/: schema and process references used by the skill..claude-plugin/marketplace.json: Claude plugin marketplace descriptor..gitignore: repo hygiene.python3 scripts/rlm_orchestrator.py --input <INPUT_DIR> --output <OUT_DIR>
npx skills)# Install this skill to all supported local agents
npx skills install Zpankz/refactor/refactor
# Install to only Claude's skills directory
npx skills install Zpankz/refactor/refactor --agent claude
# Dry-run preview
npx skills install Zpankz/refactor/refactor --agent claude --dry-run
This repo includes a Claude marketplace manifest. After publishing, a Claude user can add the marketplace and install the plugin:
/plugin marketplace add https://github.com/Zpankz/refactor
/plugin install refactor@refactor-marketplace
--mode analysis for audit-only graph extraction.--mode orchestration for recursive refinement and module extraction.--min-similarity, --target-confidence, --min-bridge-weight, --max-bridges, and max depth settings.This project does not include any secrets, credentials, or deployment keys. It is deterministic and keeps model context output artifacts on disk for traceability.
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