Remove specific pages from a PDF by their 1-based page numbers, keeping the rest in order. Returns base64.
| Name | Required | Description | Default |
|---|---|---|---|
| Yes | The PDF as a base64 string or https URL. | ||
| pages | Yes | 1-based page numbers to delete. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description mentions removing pages and returning base64 but lacks details on error handling, scope, or permissions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no extraneous information, efficiently front-loading the core operation and output.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and sibling context, the description adequately covers purpose and output; missing minor details like return format specificity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%; description adds no new meaning beyond what schema provides (e.g., page numbers already described as 1-based).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it removes specific pages from a PDF by 1-based numbers, distinguishing it from siblings like compress, merge, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool vs alternatives; usage is implied but not detailed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct PDF operation: compression, page deletion, info retrieval, merging, protection, rotation, and splitting. There is no overlap or ambiguity between tool purposes.
All tool names follow a consistent verb_noun pattern in snake_case (e.g., compress_pdf, delete_pages), making it easy to predict functionality from the name.
With 7 tools covering essential PDF manipulations, the count is well-scoped for the domain. Each tool serves a clear purpose without unnecessary redundancy.
The set covers core PDF operations (CRUD for pages, compression, protection, info). Minor gaps exist (e.g., no watermarking or annotation), but the surface is sufficient for typical workflows.
