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/migrate

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",

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mega-brain
1284 skills2 hooks
Install
$ npx -y skills add guhcostan/claude-mega-brain --skill migrate --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/migrate

Context preview

The summary Claude sees to decide when to auto-load this skill.

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",

SKILL.md

migrate.SKILL.md
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
Read more
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Python
Language
MIT
License
3mo ago
Last commit
3mo ago
Created
7h ago
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Repo: guhcostan/claude-mega-brain

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