---

name: migrate description: Scan the project and migrate existing documentation into OKF format. Use when the user wants to populate the knowledge base from existing docs, README, schemas, API specs, runbooks, or any structured project knowledge. Trigger on "migrate to okf", "populate the knowledge base", "scan my docs", "convert docs to okf", "importar documentação", "migrar para okf", "popular o knowledge base", "lê meus docs e cria o okf", "generate okf from existing docs", or when the user points at a docs folder and asks to "put it in the knowledge base". If no OKF files exist yet, run /mega-brain:init before migrating.

migrate — Migrate Existing Docs to OKF

Reads existing project documentation and generates OKF concept files so claude-mega-brain can inject them at session start. The goal is exact fidelity — preserve real column names, actual formulas, and specific values, not generic descriptions.

Before starting

Look for existing OKF files: any .md with type: frontmatter, or index.md / log.md anywhere in the project. If none exist, run /mega-brain:init first.

If .mega-brain.json defines dir, place new files under that directory. Otherwise, put files wherever fits the project (docs/, project root, etc.) — no dedicated folder is required.

Process

1. Discover sources

Scan the project root. Priority order:

Source	Look for
API specs	openapi.yaml, swagger.json, *.openapi.yml
DB schemas	schema.sql, schema.prisma, *.dbml, migration files
Data models	models/, entities/, domain/
README sections	## API, ## Schema, ## Architecture, ## Data
Runbooks	docs/runbook*, runbooks/, playbooks/
Env/config docs	.env.example with comments, annotated config/ files
Existing wikis	docs/, wiki/, pages/

Report what you found before proceeding. If more than 10 sources, ask the user to confirm before generating all files.

2. Classify each source → OKF type

Source content	OKF type
DB table / Prisma model	Table or BigQuery Table
REST/GraphQL endpoint	API
Business metric / KPI	Metric
Microservice / module	Service
Operational procedure	Runbook
Business term / glossary	Concept
Data pipeline / ETL	Pipeline

3. Generate OKF files

One .md file per concept:

---
type: <classified type>
title: <name>
description: <one sentence, plain language>
resource: <source file path or URL>
tags: [<relevant tags>]
timestamp: <today ISO date>
---

# Schema / Definition

<exact content extracted from source — preserve all field names, types, values>

# Notes

<caveats, deprecations, gotchas found in the source>

Rules that matter:

• One concept per file — split tables from each other, endpoints from each other
• Preserve exact field names, column types, enum values, formulas — never generalize
• Add wikilinks [Name](relative-path.md) when concepts reference each other
• Place files in tables/, apis/, metrics/, services/, runbooks/ as appropriate

4. Update index.md

Add one line per new concept under the relevant section in the project's existing index.md (create one via /mega-brain:init if missing):

- [Title](subdir/file.md) — one-sentence description

5. Append to log.md

<today ISO date> — migrated <N> concepts from <source list>

6. Report

List every file created with its type and path. Flag anything ambiguous or skipped with a reason.

Tell the user to start a new Claude Code session for the injected context to activate.

What NOT to migrate

• Test fixtures and mock data
• Build artifacts and generated code
• Duplicate docs — keep the most recent or canonical version
• Files with no extractable schema, formula, or definition