pdf watermark
pdf_watermarkStamp diagonal text watermark on every page of a PDF (by URL). text = the watermark.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | ||
| text | No |
pdf_watermarkStamp diagonal text watermark on every page of a PDF (by URL). text = the watermark.
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | ||
| text | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full disclosure burden. It discloses the stamping behavior but does not clarify whether the original PDF is modified, whether a new watermarked PDF is returned, what the output format is, or whether authentication is needed.
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 exceptionally concise: one sentence captures the action, scope, styling, and input source; another single sentence defines the text parameter. There is no redundant information or filler.
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?
With no annotations and no output schema, the description is incomplete. It tells the agent what the tool does but omits the tool's return value, side effects on the input PDF, and any limitation or access requirements around the URL input.
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 description partially compensates for the schema having 0% coverage: it explicitly says 'text = the watermark' and hints that the PDF is referenced by URL. However, it does not define the required format or whether the url parameter is required, leaving an important gap for a two-parameter tool.
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 and resource: 'Stamp diagonal text watermark on every page of a PDF (by URL).' It also clarifies that the text argument is the watermark, making the tool's purpose clear and differentiating it from sibling tools like pdf_add_page_numbers or pdf_to_markdown.
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?
The description implies the usage context: watermark a PDF page-by-page using a URL and text. However, it does not explicitly state when to choose this tool over alternatives, nor does it mention any exclusion conditions or prerequisites.
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.