content-extraction

name	content-extraction
description	Extract, summarize, or analyze content from a Word document without modifying it. Use when the user asks to "summarize", "list the key points", "extract action items", "what does this document say about X", "outline this document", or any read-only analysis of document content. Also use when the user asks to pull specific data from the document (tables, headings, metrics, names).
metadata	{"author":"talk2view-word","version":"1.1"}
allowed-tools	get_document get_comments search_document

Content Extraction

When to use

• User asks to "summarize", "outline", or "give me the key points"
• User asks to "extract" or "list" specific elements (action items, decisions, names, dates, metrics)
• User asks "what does this document say about X?"
• User asks for a "table of contents" or "document outline"
• User asks to compare or contrast sections within the document
• User wants to understand a document before editing it

The core problem

Extraction is read-only — you analyze the document and respond verbally. You do NOT modify the document. The temptation is to skim and guess, but the agent must read the full document systematically to avoid missing content in later sections.

Key rules

1. Read the FULL document before answering

Always start with a complete read:

get_document()

If total_paragraphs exceeds the returned count, paginate:

get_document(start_index=100, count=100)

Do not answer based on partial reads. A summary that misses the last section is wrong.

2. Use the paragraph structure as your guide

The get_document() response includes paragraph styles. Use heading styles to understand document structure:

Heading1: "Introduction"        → top-level section
  Normal: body text...
Heading1: "Financial Results"   → next top-level section
  Heading2: "Revenue"           → subsection
    Normal: body text...
  Heading2: "Expenses"          → subsection
    Normal: body text...

This heading hierarchy IS the document outline.

3. Check tables for structured data

get_document() now returns table metadata:

tables: [
  { index: 0, rows: 5, columns: 3, first_row: ["Quarter", "Revenue", "Growth"] }
]

Tables often contain the most important data — don't skip them.

4. Check comments for context

If the document has review comments, they may contain important context:

get_comments()

Comments reveal what reviewers flagged, what's been discussed, and what's unresolved.

5. Never modify the document during extraction

Extraction is read-only. Do not call insert_content, format_text, format_paragraph, delete_content, or any write tool. If the user wants changes based on your analysis, confirm first.

Step-by-step: Summarize a document

1. Read the full document:

   get_document()
   

   If paginated, read all pages.

2. Build the outline from heading styles:

   Heading1: "Executive Summary"
   Heading1: "Market Analysis"
     Heading2: "Competitive Landscape"
     Heading2: "Target Segments"
   Heading1: "Strategy"
   Heading1: "Financial Projections"
   Heading1: "Next Steps"
   

3. Identify the key message from the first section (usually Executive Summary or Introduction).

4. Note data from tables — revenue figures, timelines, comparisons.

5. Present a structured summary:

   This document is a [type] covering [topic]. Key points:
   
   - [Main finding/argument from section 1]
   - [Main finding from section 2]
   - [Key data point from table: e.g., "Revenue grew 23% to $4.2M"]
   - [Conclusion or recommended action]
   
   The document has [N] sections and [M] tables.
   

Step-by-step: Extract specific elements

Extract action items

1. Read the document:

   get_document()
   

2. Scan for action-oriented language: "will", "should", "must", "action:", "next step:", "TODO", "by [date]", "responsible:", "owner:".

3. Check tables — action items are often in tables with columns like "Action", "Owner", "Due Date".

4. Present as a list:

   Action items found:
   
   1. [Action] — Owner: [name], Due: [date] (paragraph N)
   2. [Action] — Owner: [name], Due: [date] (table 0, row 3)
   

Extract document outline

1. Read the document:

   get_document()
   

2. Filter paragraphs with heading styles (Heading1, Heading2, Heading3, Title).

3. Present with indentation:

   Document outline:
   
   Title: "Annual Report 2025"
   1. Executive Summary
   2. Financial Performance
      2.1 Revenue
      2.2 Operating Costs
   3. Strategic Initiatives
      3.1 Product Development
      3.2 Market Expansion
   4. Outlook
   

Extract data from tables

1. Read the document to find tables:

   get_document()
   // tables: [{ index: 0, rows: 5, columns: 3, first_row: ["Quarter", "Revenue", "Growth"] }]
   

2. Report the table contents using the first_row preview and row count:

   Found 1 table:
   - Table 0: 5 rows x 3 columns, headers: Quarter, Revenue, Growth
   

3. For detailed data, the full table values are available in the get_document response paragraphs and table metadata.

Extraction types

User request	What to extract	Where to look
"Summarize this"	Main argument, key findings, conclusion	Headings + first paragraph of each section
"List action items"	Tasks, owners, deadlines	Body text + tables with action/owner/date columns
"Give me the outline"	Document structure	Heading styles only
"What are the key metrics?"	Numbers, percentages, amounts	Tables + body text with numeric data
"Who is mentioned?"	Names, roles	Body text + tables
"What decisions were made?"	Decision statements	Body text near "decided", "agreed", "approved"
"What's unresolved?"	Open items, questions	Comments (get_comments) + text with "TBD", "TODO", "?"

Gotchas

• Paginate large documents. If total_paragraphs > 100, you only got the first 100. Call get_document(start_index=100, count=100) to get the rest.
• Tables may contain the most important data. Don't skip them in your summary.
• Comments are separate from body text. Call get_comments() if the user asks about feedback, issues, or unresolved items.
• Don't confuse heading text with body text. A heading paragraph like "Revenue" is a section label, not a content statement.

Common mistakes

Mistake	Why it's wrong	Fix
Summarizing from the first few paragraphs only	Misses key content in later sections	Read the full document; paginate if needed
Not checking tables	Tables often contain the key data	Always check table metadata in get_document response
Modifying the document during extraction	User asked for analysis, not changes	Only use read tools (get_document, get_comments, search_document)
Giving a vague summary	"The document discusses several topics" is useless	Include specific findings, numbers, and section references
Not mentioning unresolved comments	User may not know there's open feedback	Check get_comments and report unresolved items