Skip to main content
Glama

generate_change_summary

Produce an email-ready change log by reading tracked modifications in a Word document, grouping adjacent deletions and insertions as replacement entries.

Instructions

Summarise tracked changes already present in the open document as an email-ready .txt.

Use this after making edits with tracked=True (the default) and saving, to produce a human-readable change log of what was modified. Reads the document's existing w:ins / w:del elements, groups adjacent deletion+insertion pairs as REPLACEMENT entries, and writes a numbered list with author, date, and text per change.

Typical workflow: open_document → edit with tracked=True → save_document → generate_change_summary

If you have two separate files to compare rather than an already-edited document, use diff_to_text instead.

Args: output_path: Destination .txt path. Auto-generated from the document stem if empty. document_handle: Optional handle for concurrent session isolation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
output_pathNo
document_handleNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Describes internal behavior: reading w:ins/w:del elements, grouping deletion+insertion pairs as replacements, and outputting a numbered list with author, date, and text. With no annotations provided, the description carries the burden well, though it omits details like prerequisites (e.g., document must contain tracked changes) and error handling.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is relatively concise, front-loading the purpose, followed by usage guidance and parameter details. Every sentence adds value, though it could be slightly more trimmed without losing clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the presence of an output schema, the description adequately covers when to use, behavior, and parameter semantics. It tells the agent what the output contains (numbered list with author, date, text). However, it could mention prerequisites or conditions for a successful invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% (parameters only have default and title in schema), but the description adds meaning: output_path destination .txt path (auto-generated from document stem if empty) and document_handle for concurrent session isolation. This compensates for the lack of schema documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: summarizing tracked changes in an open document into an email-ready .txt file. It includes specific details about the output format and distinguishes itself from the sibling tool diff_to_text.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly provides when to use (after editing with tracked=True and saving) and a typical workflow: open_document → edit with tracked=True → save_document → generate_change_summary. Also explicitly advises use of diff_to_text for comparing separate files.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/SecurityRonin/docx-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server