pdf page count
pdf_page_countCount pages and report each page size of a PDF (by URL).
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| url | No |
pdf_page_countCount pages and report each page size of a PDF (by URL).
| Name | Required | Description | Default |
|---|---|---|---|
| url | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Count' and 'report' imply a non-destructive read operation, but the description does not disclose network-fetching behavior, error handling for invalid URLs or non-PDFs, or the units/format of reported page sizes.
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?
The description is a single front-loaded sentence with no filler: it states the verb, target, and output intent directly. Every word contributes to understanding the tool.
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?
For a one-parameter, read-only utility, the description covers the essential input (URL) and output (page count and per-page sizes). It is not fully complete because there is no output schema and the exact return structure is implicit, but the low complexity makes the one-liner nearly sufficient.
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?
The input schema exposes only a bare `url` property with no type, description, or required flag, and schema coverage is 0%. The description's '(by URL)' adds minimal clarification over the property name and does not specify URL schemes, requiredness, or how additional properties should be handled.
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?
The description uses a specific verb ('Count') and resource ('pages ... of a PDF'), and also specifies the output behavior ('report each page size'). This clearly distinguishes it from sibling PDF tools such as pdf_to_markdown or pdf_add_page_numbers.
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?
It is clear that the tool is for page counting and page-size reporting, and that the PDF is accessed by URL. However, no explicit when-to-use guidance or comparison with alternative tools is provided; the usage context is implied rather than stated.
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 unique operation—conversions, extractions, translations, and utilities like resume checking or redaction—with no meaningful overlap. The few similar tools (e.g., convert_to_pdf vs. xlsx_to_pdf) are clearly distinguished by input type.
Naming mixes conventions: verb_noun (extract_tables, redact_text), noun_to_noun (xlsx_to_pdf, pptx_to_pdf), and unusual forms like doc_translate_cn and what_can_you_do. While snake_case is consistent, the verb/noun pattern is not, making the set slightly less predictable.
With 23 tools, the server sits at the heavy end of the acceptable range. Every tool has a distinct purpose, but the spread across PDF handling, research, audio, and accounting utilities feels more like a miscellaneous collection than a focused suite, which could overwhelm agents.
The server covers a broad spectrum of document-processing tasks—conversion, extraction, translation, redaction, and validation—with few dead ends. Minor gaps exist (e.g., no PDF merge/split, no OCR for all scanned PDFs, no explicit delete/update for resources), but core workflows are well supported.