extract-doc

name	extract-doc
description	Extract reusable insights from a single external doc or page into ARIA intake entries. Trigger on /extract-doc or extract insights from this Notion, Google Doc, or Confluence page.
argument-hint	<doc-url-or-id> [tags]
allowed-tools	Read, Write, Grep

/extract-doc — Extract Insights from a Doc to Intake Backlog

RETIRED 2026-06-21 (v2.33.0). Folded into /intake: extract-doc → /intake extract <doc-url> (decompose a source into backlog entries). Kept for reference only — not a live skill (archived under skills/.archived/, excluded from discovery).

Pull knowledge-worthy items from a single connected ~~docs source (Notion page, Google Doc, Confluence page, Box doc, Egnyte file) into intake/insights-backlog.md. Unlike /intake doc (which captures the doc itself as one structured artifact for later reaction), /extract-doc decomposes the doc into N intake entries — one per insight, decision, or question worth surfacing at audit.

Step 0: Resolve Config

Read ~/.claude/aria-knowledge.local.md and extract knowledge_folder. If the file doesn't exist, stop: "aria-knowledge is not configured. Run /setup to get started."

Verify {knowledge_folder}/intake/insights-backlog.md exists. If not, stop: "Insights backlog not found. Run /setup to repair the knowledge folder structure."

Step 1: Probe Connected MCPs

Check Codex's available tool list for ~~docs MCPs:

• ~~docs (notion, atlassian, box, egnyte, google docs): if connected, available for doc fetch.

If NO ~~docs MCP is connected, output the standard fallback notice and stop:

No required MCPs connected for /extract-doc. Connect one of: Notion, Atlassian (Confluence), Box, Egnyte, or Google Docs (when available) via Codex MCP configuration. See CONNECTORS.md. Skipping this run.

Per ADR-015.

Step 2: Parse Input

The user provides one of:

• A Notion page URL — https://www.notion.so/<workspace>/<title>-<id> or notion.so/<id>
• A Confluence page URL — https://<org>.atlassian.net/wiki/spaces/<space>/pages/<id>/<title>
• A Google Docs URL — https://docs.google.com/document/d/<doc-id>/... (if google docs MCP wired; placeholder URL in v2.18.0 .mcp.json)
• A Box file URL — https://app.box.com/file/<file-id>
• An Egnyte file URL — https://<org>.egnyte.com/...
• A bare doc/page ID — opaque string the connected MCP can resolve

Optionally followed by tags (e.g., engineering postmortem, cs onboarding).

Source-type detection:

Input shape	Routes to
Contains notion.so or www.notion.so	~~docs (notion)
Contains atlassian.net/wiki	~~docs (atlassian)
Contains docs.google.com/document	~~docs (google docs)
Contains app.box.com/file	~~docs (box)
Contains egnyte.com	~~docs (egnyte)
Ambiguous	Ask user which ~~docs MCP holds the doc

If the detected-source's MCP is not connected, output a specific fallback notice:

This doc looks like a [Notion / Confluence / etc.] page but the [vendor] MCP is not connected. Connect [vendor] via your MCP config and retry, or paste the doc URL of a different format. Skipping this run.

Step 3: Fetch Doc Content

Call the connected MCP's page/doc-fetch tool with the resolved ID:

• Notion: notion.fetch or pages.retrieve + blocks.children.list for body.
• Atlassian: confluence.pages.get (or equivalent) — request body in storage/representation that preserves headings + lists.
• Google Docs: documents.get — extract text content + structure.
• Box / Egnyte: file content fetch + text extraction (skip binary attachments).

Gather:

• Doc title
• Author (last editor) + last-edited timestamp (if exposed)
• Workspace / space / parent context (e.g., "Notion → Engineering → 2026 Q2")
• Body content as structured text (preserve headings, lists, links — flatten complex blocks)

Limit: if the doc is >20KB of extracted text, fetch the first 20KB + note the truncation in the entry metadata. The user can re-invoke with a section anchor (#heading) for the tail.

Step 4: Extract Insights

Read the doc body and identify knowledge-worthy items — discrete propositions worth surfacing at next /audit-knowledge. Each candidate should be a single self-contained claim, decision, lesson, or question.

For each candidate, classify into one of the standard intake categories:

Category	Use when
insight	Observation about how something works, or a learning
decision	A choice that was made + rationale
extraction	A pattern, recipe, or how-to worth promoting later
idea	A "we should consider X" proposition
reference	A useful URL or external resource named in the doc

Quality bar: skip items that are project-status updates, ephemeral context, or items already obviously in the knowledge folder. Default to fewer-but-stronger — extracting 3 strong items beats 12 weak ones.

Step 5: Stage to Backlog + Report

For each extracted item, append a new entry to {knowledge_folder}/intake/insights-backlog.md (or decisions-backlog.md / extraction-backlog.md per category; ideas go to intake/ideas/<date>-<slug>.md per v2.11.0 per-file convention).

Standard intake entry format (mirrors /extract skill output):

## <one-line claim or title>

- **Source:** [<doc-title>](<doc-url>) ([<vendor>])
- **Date captured:** <YYYY-MM-DD>
- **Project tags:** <from input args + auto-detected from doc workspace>
- **Original context:** <2-3 sentence excerpt from the doc giving the surrounding context>

<the insight itself, 1-3 sentences, in the user's voice as inferred from the doc>

For idea candidates (per v2.11.0 per-file convention), write {knowledge_folder}/intake/ideas/{date}-{slug}.md:

---
date: <YYYY-MM-DD>
project: <tag>
type: <category>
title: <slug-shaped title>
source: <doc-url>
---

**Proposal:** <the idea>

**Motivation:** <why this matters per the doc context>

**Source:** [<doc-title>](<doc-url>) via /extract-doc

Report to user:

Extracted <N> items from <doc-title> (<vendor>):

| Category | Count | Routed to |
|---|---|---|
| insight | <n> | intake/insights-backlog.md |
| decision | <n> | intake/decisions-backlog.md |
| extraction | <n> | intake/extraction-backlog.md |
| idea | <n> | intake/ideas/<date>-*.md |
| reference | <n> | intake/insights-backlog.md (will route to references/ at audit) |

Next: review at next /audit-knowledge run. The standard disposition vocabulary (Accept → tracker / roadmap / todo / adr / plan / bundle / rule / Defer / Reject) applies.

Rules

• Never auto-promote. Items stay in intake/*-backlog.md until /audit-knowledge routes them.
• Never modify the source doc. Read-only externally.
• Strip secrets if obvious — same redaction rules as /clip-thread.
• One doc per invocation. For bulk, use /intake with a directory or glob of doc URLs.
• Default fewer-but-stronger. Better to surface 3 substantial items for audit than 15 trivial ones — audit cycles cost user attention.

Notes

• Bidirectional per ADR-014 — aria-cowork v0.4.0 imports byte-faithfully.
• Output schema is byte-identical across plugins per ADR-013. Both plugins write to the same insights-backlog.md / decisions-backlog.md / extraction-backlog.md / intake/ideas/*.md files in the shared knowledge folder.
• Probe semantics per ADR-015.
• Composes with /audit-knowledge — extracted items follow the same disposition vocabulary as any other intake entry. The Source: field is preserved through routing.
• Differs from /intake doc mode (v2.17.0+): /intake doc captures ONE structured artifact per doc with user-fillable reaction section; /extract-doc decomposes a doc into MULTIPLE intake entries for audit routing. Use /intake doc when you want to react to a doc as a whole; use /extract-doc when the doc contains many discrete items worth surfacing separately.