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daekeun-ml

PowerPoint Translator

by daekeun-ml

export_powerpoint_markdown

Convert a PowerPoint .pptx file into structured Markdown, enabling AI-friendly notes or deterministic content extraction with optional web verification.

Instructions

Export one PowerPoint presentation as structured Markdown.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNo"structured" for AI notes or "extract" for deterministic extractionstructured
workersNoConcurrent slide-summary chunks
model_idNoBedrock Mantle model used for structured modeopenai.gpt-5.6-terra
cache_pathNoOptional SQLite cache path
input_fileYesPath to a .pptx file
web_verifyNoRun bounded client-side web verification
output_fileNoMarkdown output path; generated beside the PPT when omitted
cache_backendNosqlite, memory, or nonesqlite
max_web_queriesNoMaximum search queries when web_verify is enabled
output_languageNoLanguage code for AI notes, or "source"ja
slides_per_chunkNoSlides supplied to each summary request

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries the burden of explaining behavior. It only discloses that a PowerPoint is exported to Markdown, but fails to mention that the tool may invoke an AI model, perform web verification, write output files, use a cache, or have side effects. These behaviors are important for agent decision-making and are not transparent.

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 one concise, front-loaded sentence with no filler. It does not waste space, though for a tool with 11 parameters and important behavioral differences, a slightly richer description would be more appropriately sized.

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?

This is a complex tool with many options (mode, workers, model, caching, web_verify, output_language, chunking) and no annotations. The one-sentence description is not enough to let an agent know when to choose single export vs batch, or what operational trade-offs exist. The presence of an output schema helps, but the description still leaves substantial contextual gaps.

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?

Parameter schema coverage is 100%, with descriptions for all parameters, so the schema already explains each parameter. The tool description adds no parameter-level nuance beyond saying 'structured Markdown', so a baseline score of 3 is appropriate.

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 states a concrete action ('Export'), a clear resource ('one PowerPoint presentation'), and a specific output ('structured Markdown'). The word 'one' distinguishes it from the sibling batch_export_powerpoint_markdown tool, making the intended scope unambiguous.

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

Usage Guidelines2/5

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

The description provides no guidance on when to prefer this tool over alternatives such as batch_export_powerpoint_markdown or translate_powerpoint. It also does not mention the 'structured' vs 'extract' modes as usage decisions, leaving the agent to infer mostly from parameter defaults.

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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