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withsivram

GoodNotes MCP Server

by withsivram

read_page

Extract OCR text from a specific page in a GoodNotes notebook using the notebook ID and page number. Retrieve handwritten content for AI analysis or search.

Instructions

Read OCR text from a single page of a GoodNotes notebook.

Args: notebook_id: The document UUID page_number: Page number (1-indexed)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
notebook_idYes
page_numberYes

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 behavioral disclosure. It indicates a read-only operation via the verb 'Read', but does not explicitly state that it is non-destructive or address edge cases like invalid page numbers or missing notebooks. Some context is given (1-indexed pages), but more detail would improve transparency.

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 remarkably concise, consisting of a single sentence plus an Args block. Every sentence earns its place, and the structure is front-loaded with the primary purpose first. No redundant or extraneous information is present.

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 simple two-parameter read tool, the description is almost complete. It explains both parameters and the core functionality, and an output schema exists to define return values. However, it lacks explicit usage guidance and does not describe error handling or behavioral nuances, which prevents a perfect score.

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?

Since the input schema has no property descriptions (0% coverage), the description must compensate. It does so by explaining notebook_id as 'The document UUID' and page_number as 'Page number (1-indexed)', adding semantic meaning beyond the raw types. This is helpful, though not exhaustive in describing formats or constraints.

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: 'Read OCR text from a single page of a GoodNotes notebook.' It specifies the verb (read), the resource (OCR text), and the scope (single page), which distinguishes it from siblings like read_notebook. The purpose is immediately understandable and 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 use this tool versus alternatives such as read_notebook or search_notes. It does not mention any exclusions or conditions, leaving the agent to infer usage solely from the tool name and basic description.

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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