Convert public PDF links into Markdown with page counts and explicit excerpt limits.
Scored across 1 tool
There is only one tool, so there is no possibility of confusing it with another. Its purpose (convert a public PDF URL to Markdown) is unambiguous and clearly stated.
The single name convert_pdf_url follows a clean snake_case verb_noun convention. With only one tool there is no conflicting pattern to break consistency.
A single tool is thin even for a narrow PDF-to-Markdown utility; converting from URLs is the only entry point. The scope is focused but leaves no alternative paths (e.g. local file or batch), making it borderline under-provisioned.
Core conversion from a public URL is covered, but there is no local file input, no OCR for scanned documents, and no batch or multi-source handling despite scanned pages being detected. These are notable gaps an agent must work around.
Convert a PDF available at a public HTTP or HTTPS link into Markdown for reading, research or a coding project. Returns extracted text, page and table counts, and whether scanned pages were found. No OCR, private links or local files. The reply is limited to 20,000 Markdown characters and marks longer results as excerpts; the whole PDF uses the API page allowance.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes |
| Name | Required | Description |
|---|---|---|
| pages | No | |
| status | Yes | |
| tables | No | |
| message | Yes | |
| docs_url | Yes | |
| markdown | No | |
| truncated | No | |
| source_url | No | |
| http_status | No | |
| retry_after | No | |
| converted_at | No | |
| scanned_pages | No | |
| parser_version | No | |
| remaining_pages | No | |
| total_characters | No | |
| returned_characters | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations, the description discloses important behavioral constraints: no OCR support, no private links or local files, results capped at 20,000 Markdown characters, longer results marked as excerpts, and the whole PDF counting against the API page allowance. These details materially affect invocation expectations and are not present in the structured annotations.
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 four compact sentences, front-loading the core action and then layering constraints and output behavior. Every sentence contributes useful information without repetition.
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 tool with an output schema, the description covers the action, input restrictions, output format, truncation behavior, and API limits. Even though an output schema exists, the return summary is useful and nothing essential for correct invocation is missing.
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?
With one parameter and 0% schema description coverage, the description compensates by clarifying that the input must be a public HTTP or HTTPS link and excluding private links and local files. It does not mention the 2048-character maxLength or the URI format, but it adds meaningful semantic constraints beyond the bare schema.
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 states a specific verb and resource: convert a PDF from a public HTTP or HTTPS link into Markdown. It also names the supported input scope (public links only) and the output format, so an agent can identify exactly what the tool does without inspecting the schema.
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 gives usage context ('for reading, research or a coding project') and explicit exclusions ('No OCR, private links or local files'), which tell the agent when not to use it. It does not compare against alternatives, but no sibling tools exist, so this is a clear contextual guide.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
convert_pdf_urlExtract PDFs to Markdown, RAG chunks and cited tables; publish tracked Doc Links with read stats.
PDF URLs to per-page text, tables as rows, Markdown, metadata and OCR for scanned pages.
Convert PDF URLs to clean Markdown and text for RAG and LLM input. Pay per PDF on Apify.
Link-preview metadata and clean page-to-Markdown for any public URL. No install.
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