Skip to main content
Glama

pdf_compress

Reduce PDF size by choosing a compression level: screen (smallest), ebook (default), printer, or prepress (largest). Save space and share easier; costs 1 cent.

Instructions

Shrink a PDF. Levels: screen (smallest), ebook (default, good for sharing), printer, prepress (largest, best quality). 1 cent.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fileYes
levelNoebook
output_pathNo
idempotency_keyNo
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 transparently discloses a cost per call ('1 cent') and explains the trade-offs among the compression levels (smallest vs. largest, quality). However, it does not describe whether the input file is modified, whether output_path is required, or what the operation returns, which limits 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 extremely concise, using three short sentences to cover the core action, the main parameter options, and the cost. The purpose is front-loaded in the first phrase, with supporting details following in a logical order. Every sentence adds information without redundancy.

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 4-parameter tool with no annotations and no output schema, so the description needs to be relatively complete. It covers the action, levels, and cost, but omits how the output file is named or returned, and the role of 'idempotency_key'. The absence of any mention of 'output_path' or the result format means an agent cannot fully determine correct invocation without additional assumptions.

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

Parameters2/5

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

The input schema has 0% description coverage, so the description must compensate. It provides meaningful semantics for the 'level' parameter, mapping each enum value to a size/quality trade-off and identifying the default. However, it gives no semantic information for 'file', 'output_path', or 'idempotency_key', leaving those parameters under-specified.

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 specific verb ('Shrink') and resource ('a PDF'), which directly names the operation. It also enumerates four distinct compression levels, further clarifying what the tool does. This distinguishes it clearly from sibling PDF tools like merge, split, rotate, and image conversion.

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 over its siblings (e.g., pdf_merge, pdf_split). It does offer level-specific advice ('ebook... good for sharing'), but that addresses parameter selection, not tool selection. There are no explicit exclusions or alternatives mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/BiGapi-2026/bigapi-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server