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keigoly

pdf-chapter-splitter

by keigoly

get_toc

Extract a PDF's table of contents to get a hierarchical chapter outline with page numbers, enabling structured navigation before splitting into sections.

Instructions

Extract table of contents (bookmarks/outline) from a PDF. Returns hierarchical chapter structure with page numbers.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_pathYesAbsolute path to the PDF file

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.0

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It states that the tool extracts the TOC and returns hierarchical structure with page numbers, which implies a read-only operation and provides some output expectations. However, it does not disclose what happens when a PDF has no bookmarks, whether it scans the text if bookmarks are absent, or any error behavior. This is a meaningful gap for a tool with no annotation safety hints.

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 a single, tightly worded sentence that front-loads the core action (extract TOC) and immediately gives the key output detail (hierarchical structure with page numbers). Every part adds value, and there is no repetition or filler.

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 tool with one well-documented parameter and no output schema, the description adequately conveys the purpose and the general shape of the return value. It does not mention edge cases like PDFs without bookmarks, but the core usage scenario is clear enough for an agent to make a confident call.

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%, with the only parameter, file_path, already clearly documented as 'Absolute path to the PDF file'. The tool description adds no additional meaning or nuance to the parameter. Baseline score of 3 is appropriate since the schema handles this dimension completely.

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 clearly specifies the verb 'Extract' and the resource 'table of contents from a PDF', and it states the return value as a hierarchical chapter structure with page numbers. However, it does not explicitly distinguish itself from the sibling tool list_chapters, which may perform a similar function. The level of specificity is high, but lacking direct sibling differentiation prevents a perfect score.

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?

There is no guidance about when to use this tool versus its siblings. The description neither mentions alternatives nor provides context such as 'use this for embedded bookmarks' or 'prefer list_chapters when only chapter names are needed.' The agent is left to infer appropriate usage from the name and description alone.

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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