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daekeun-ml

PowerPoint Translator

by daekeun-ml

post_process_powerpoint

Fix text overflow in PowerPoint presentations by enabling text wrapping and shrink-to-fit for text boxes containing long content.

Instructions

Apply post-processing to a PowerPoint presentation to optimize text boxes.

This function enables text wrapping and shrink text on overflow for text boxes that contain text longer than the specified threshold.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
input_fileYesPath to the input PowerPoint file (.pptx)
output_fileNoPath to save the processed file (optional, auto-generated if not provided)
enable_autofitNoEnable text auto-fitting (default: True)
text_thresholdNoText length threshold for enabling auto-fit (overrides .env setting)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavior disclosure. It does disclose the core behavioral effect — enabling text wrapping and shrink-on-overflow for qualifying text boxes. However, it does not mention whether the input file is modified in place, how the auto-generated output path behaves, or any side effects on existing autofit settings, leaving a mild gap for a mutation tool.

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?

Two front-loaded sentences with zero filler. The first sentence states the operation and resource, the second immediately gives the concrete behavior and the condition that triggers it. Every part of the description earns its place.

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?

For a tool with 4 fully-schema-covered parameters and no output schema needing explanation, the description communicates the purpose, target behavior, and the threshold condition. Minor omissions are details such as where the auto-generated output path is written and the meaning of the .env fallback for the threshold, but nothing that would prevent an agent from invoking the tool correctly.

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

Parameters3/5

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

Schema description coverage is 100%, so the baseline is 3 and the schema already documents all four parameters. The description does add useful context by tying the threshold concept to the tool's trigger condition ('text longer than the specified threshold'), which clarifies text_threshold's role. But it offers no extra format, syntax, or edge-case details beyond what the schema already provides.

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

Purpose4/5

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

The description states a clear operation on a specific resource: 'Apply post-processing to a PowerPoint presentation' and concretely defines what that means with 'enables text wrapping and shrink text on overflow'. It is easily distinguishable from the sibling tools, which are all translation/export operations, so an agent can tell this is the text-box optimization tool. The one weakness is the generic initial verb 'Apply post-processing' before the more specific detail.

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

Usage Guidelines3/5

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

There is no explicit when-to-use vs alternative statements, no exclusions, and no mention of the sibling translation/export tools. However, usage is strongly implied by the content: the description defines the trigger condition ('text boxes that contain text longer than the specified threshold'), and the sibling set is clearly for different tasks, making the intended context reasonably inferable.

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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