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Get Tracking Changes In Word

get_tracking_changes_in_word

Extract tracked changes from Word documents to identify insertions, deletions, and formatting edits. Saves the data as JSON.

Instructions

Extract tracking changes data from a Word file via PDF4me /api/v2/GetTrackingChangesInWord. Input is a local .docx/.doc file. Saves the API response as JSON (or raw text fallback).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
output_dirNo
word_file_pathYes
output_file_nameNo
request_doc_nameNo
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses that the API response is saved as JSON with a raw text fallback, which is useful behavioral information. However, it does not mention whether the original file is modified, what error handling occurs, or any prerequisites like network access or authentication. Some transparency is present, but gaps remain.

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

Conciseness5/5

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

The description is only two sentences, uses concise phrasing, and front-loads the core purpose first. Every sentence adds value: the first states the action and API, the second gives input/output specifics. No fluff or repetition.

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

Completeness2/5

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

With no annotations, no output schema, and zero parameter descriptions, the description is the only context for usage. It provides the basic workflow but omits important details such as the structure of the tracking changes data in the response, how output_dir and output_file_name interact, and any usage caveats. For a 4-parameter tool, this is insufficient.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It clarifies that word_file_path refers to a local .docx/.doc file and implies output_dir/output_file_name relate to saving the JSON response. However, it does not explain request_doc_name at all, and with four parameters, the description covers only about half of them, leaving the agent without meanings for the rest.

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 function with a specific verb ('Extract') and resource ('tracking changes data from a Word file'). It also distinguishes itself from sibling tools like enable/disable_tracking_changes_in_word and extract_text_from_word by focusing specifically on extracting tracking-change data.

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

Usage Guidelines4/5

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

The description gives clear context by specifying the input type (.docx/.doc) and the output behavior (saves API response as JSON). It doesn't explicitly name alternatives or say when not to use it, but the purpose is self-evident relative to the sibling tools, earning a 4.

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

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