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anananaTERRA

mcp-indesign-agent

by anananaTERRA

analyze_page

Classify page items into semantic roles for targeted batch edits. After scanning a document, label elements like headers, images, and captions to enable role-based actions.

Instructions

Classify page items into semantic roles (Header, Subtitle, Body, Caption, Image, Background, Logo, Decorative, Unknown) and store them on the Document Model. Call after scan_document so batch targets like {role:"Header"} work. Typical flow: scan → analyze_page → execute_batch → summarize_changes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
persistNoWrite roles into session cache (default true)
pageIndexYes0-based page index to analyze
Behavior3/5

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

With no annotations, the description carries the burden. It discloses that the tool classifies items and stores them on the Document Model, and implies a dependency on scan_document. However, it does not detail side effects like overwriting existing roles, reversibility, or the effect of the 'persist' parameter, leaving some transparency gaps.

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 concise and well-structured. It front-loads the main purpose, includes the list of roles for clarity, and then provides the workflow in a compact arrow sequence. Every sentence adds value without redundancy.

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 2 parameters, no output schema, and no annotations, the description is quite complete. It explains what the tool does, the prerequisite (scan_document), and how it fits into the broader pipeline. It could mention more about error conditions or the persist default, but these are minor 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?

The input schema provides 100% coverage for both parameters (pageIndex and persist), so the baseline is 3. The description does not add extra meaning beyond listing the roles; it only indirectly relates to 'persist' via 'store them on the Document Model.'

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: 'Classify page items into semantic roles' and 'store them on the Document Model.' It uses a specific verb (classify) and resource (page items), and distinguishes itself from siblings by outlining its position in the workflow with scan_document and execute_batch.

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?

Provides explicit usage guidance: 'Call after scan_document' and shows the typical flow 'scan → analyze_page → execute_batch → summarize_changes.' This clearly identifies when to invoke it, though it doesn't mention explicit alternatives or exclusions.

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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