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/ingest

Create or update a single OKF concept file from raw input. Use when the user wants to document a specific table, metric, API, service, or concept in the knowledge base — even if they say "add this to the okf", "documenta essa tabela", "cria um conceito pra isso", "adiciona no

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From plugin
mega-brain
1284 skills2 hooks
Install
$ npx -y skills add guhcostan/claude-mega-brain --skill ingest --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/ingest

Context preview

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

Create or update a single OKF concept file from raw input. Use when the user wants to document a specific table, metric, API, service, or concept in the knowledge base — even if they say "add this to the okf", "documenta essa tabela", "cria um conceito pra isso", "adiciona no

SKILL.md

ingest.SKILL.md
name: ingest
description: Create or update a single OKF concept file from raw input. Use when the user wants to document a specific table, metric, API, service, or concept in the knowledge base — even if they say "add this to the okf", "documenta essa tabela", "cria um conceito pra isso", "adiciona no knowledge base", "register this API", or pastes a schema/description and says to save it. If no OKF files exist yet, suggest /mega-brain:init first.

ingest — OKF Concept Writer

Turns raw input (schema dump, API doc, user description, table definition) into one OKF-formatted `.md` file committed to the knowledge base.

Before writing

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

If `.mega-brain.json` defines `dir`, save new concepts under that directory. Otherwise, choose a sensible location (`docs/`, project root, etc.) consistent with existing OKF files.

Check if a concept with the same name already exists. If so, ask whether to update it or create a new one.

Output format

One `.md` file per concept. Only `type` is required:

---
type: <concept type>
title: <display name>
description: <one sentence, plain language, no jargon>
resource: <URL to the actual resource, if any>
tags: [<tag1>, <tag2>]
timestamp: <ISO 8601 date>
---

<body: exact schema, formula, join patterns, examples, caveats>

Common types

| Type | Use for | |------|---------| | `BigQuery Table` | BQ tables with schema | | `BigQuery Dataset` | BQ datasets | | `Table` | Non-BQ database tables | | `Metric` | KPI or business metric with formula | | `API` | REST/GraphQL endpoints | | `Runbook` | Operational procedures | | `Concept` | Business or domain terminology | | `Service` | Internal microservices | | `Pipeline` | ETL or data pipelines |

Types are freeform — add your own.

Process

1. Read the source material 2. Identify the concept type and canonical name 3. Write `description`: one sentence, plain language 4. Add `resource` URL if there's a live resource (BQ console URL, API endpoint, dashboard) 5. Write the body with exact values — preserve field names, types, and formulas as-is; do not generalize 6. Link to related concepts with `[Name](relative-path.md)` — this builds the knowledge graph 7. Save next to related OKF files (e.g. `docs/tables/<slug>.md` or `<config-dir>/tables/<slug>.md`) 8. Add one line to `index.md`: `- [Title](path) — description` 9. Append to `log.md`: `<date> — added <title>`

Updating an existing entry

  • Update `timestamp`
  • Preserve existing wikilinks unless explicitly removing them
  • Keep `description` to one sentence — push additional detail into the body
Read more
Ships withmega-brain

Loads the knowledge. Skips the search. 100% accuracy · 0 tool calls · −66% tokens vs Obsidian+MCP Real agentic sessions. Benchmark →

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Stats
128
Stars
18
Forks
Maintained
Maintenance
Python
Language
MIT
License
3mo ago
Last commit
3mo ago
Created
7h ago
Added

Repo: guhcostan/claude-mega-brain

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