What problem does it solve? AI coding agents often generate code from generic best-practice templates that clash with a project's established house style, producing inconsistent, un-mergeable code. This Skill reconciles generic per-language playbooks against the project's actual most-recently-modified files so generated code matches the existing codebase. ## Core Features & Use Cases - Convention reconciliation: Splits playbook rules into Conventions (project style wins on conflict) and Invariants (security/correctness rules that always apply), then flags real conflicts for the user. - Per-language pattern cache: Writes .claude/orc/patterns/<lang>-pattern.md files covering React, Next.js, Vue, Angular, FastAPI, Django, NestJS, Express, Go, and Postgres, reused by every future ORC run with drift detection and --refresh support. - Subagent-based codification: Dispatches a dedicated codifier subagent to scan representative files, keeping the orchestrator's context lean, with consent-gated scanning and a language-agnostic fallback when declined. - Use Case: Before ORC executes tasks in a FastAPI + React monorepo, run the pattern codifier once so every executor writes endpoints and components that follow the project's actual router layout, naming, and validation style. ## Quick Start Ask the agent to run /orc-pattern to learn and cache this project's code conventions for all detected languages.