PDF and web tools for AI agents: extract, merge/split, forms, HTML to PDF, URL to Markdown, scrape.
Extract the text content of a PDF — for RAG, summarization, or search. Accepts a file_id (from a prior tool) or a base64-encoded PDF, and returns the text inline. Not OCR: a scanned/image-only PDF returns little or no text.
| Name | Required | Description | Default |
|---|---|---|---|
| Yes | A file_id from a prior tool result, or a base64-encoded PDF. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fully bears the responsibility for behavioral disclosure. It transparently states the output ('returns the text inline') and the limitation ('Not OCR'), giving agents a clear picture of expected behavior.
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 highly concise, using two sentences that front-load the core purpose and then add practical details (input forms, limitation). No redundant information; every sentence earns its place.
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 simple tool with no output schema, the description provides all necessary context: what it does, how to provide input, what to expect as output, and a critical limitation. An agent can confidently decide when and how to invoke it.
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 single parameter 'pdf' is described in the schema with clear meaning ('file_id from a prior tool result, or a base64-encoded PDF'), and the description reinforces this. This adds semantic value beyond the bare type, fully covering the parameter's purpose.
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 clearly states the action ('Extract the text content of a PDF') and specifies the resource, distinguishing it from siblings like rotate_pdf or merge_pdfs. It also mentions common use cases (RAG, summarization, search), making the purpose explicit.
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 provides explicit guidance on when to use the tool (for PDFs with text content) and when not to (scanned/image-only PDFs, since it's not OCR). It also clarifies input options (file_id or base64), leaving no ambiguity about usage scope.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fill a PDF's form fields from a map of field -> value; optionally flatten. Returns a file_id and a ~1h URL.
| Name | Required | Description | Default |
|---|---|---|---|
| Yes | A file_id from a prior tool result, or a base64-encoded PDF. | ||
| fields | Yes | Map of field name to value. | |
| flatten | No | Flatten the form after filling (default false). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden. It mentions the optional flatten behavior and the return of a file_id/URL, but does not disclose potential side effects, how it handles missing fields, or whether it preserves the original file. This is adequate but not comprehensive.
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 one concise sentence that front-loads the main verb and resource, followed by key options and return values. No unnecessary words or 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?
The description covers the essential inputs, the optional flattening, and the return type (file_id and URL). It lacks detail on error cases or edge scenarios, but given the simplicity of the tool and absence of an output schema, it is reasonably complete.
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 schema provides 100% coverage of all parameters (pdf, fields, flatten) with descriptions. The tool description itself does not add extra detail beyond what is already in the schema, so it meets the baseline for high schema coverage.
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 clearly states the tool's purpose: filling a PDF's form fields with a map of field-value pairs, with an optional flatten option, and it returns a file_id and URL. This is unambiguous and differs from sibling tools such as read_pdf_form.
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 does not explicitly state when to use this tool versus alternatives (e.g., read_pdf_form). It implies usage through its purpose but lacks explicit guidance or contrast with sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Combine PNG/JPEG images (base64) into a PDF, one image per page. Returns a file_id and a ~1h URL.
| Name | Required | Description | Default |
|---|---|---|---|
| images | Yes | Base64-encoded PNG/JPEG images, one per page (max 20). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool returns a file_id and a time-limited URL, which covers the main behavior and output. It does not mention potential side effects or failure modes, but none are particularly expected for this operation.
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 clearly communicate the action, input, output, and URL expiration. No filler or redundant wording.
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 simple single-parameter tool with no output schema, the description sufficiently covers the input type, page layout, limit, and return value. It provides enough context to use the tool correctly.
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 schema already provides complete coverage of the single parameter, including base64 format, accepted types, layout, and max count. The description adds only the verb 'combine', which is a marginal addition beyond the 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?
Clearly states the tool's function: combining PNG/JPEG base64 images into a PDF with one image per page. This distinguishes it from PDF-focused sibling tools like merge_pdfs or url_to_pdf.
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 makes the primary use case clear (converting images to PDF) and implies when it should be used. It does not explicitly mention alternatives, but the image-to-PDF purpose is unambiguous enough for correct selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Render Markdown to a clean, print-styled PDF. Returns a file_id and a ~1h URL.
| Name | Required | Description | Default |
|---|---|---|---|
| title | No | Document title. | |
| markdown | Yes | The Markdown to render. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry the full burden. It does disclose the output format (file_id and a ~1h URL), which is useful behavioral context. However, it omits details like synchronous vs async behavior, rate limits, size constraints, or whether the URL is a download link. For a simple conversion tool this is minimal but not severely lacking.
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 sentence that is front-loaded with the core action and includes the most important behavioral detail (return format). There is zero waste; every word contributes to understanding the tool's purpose.
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 simple conversion tool with no output schema, the description adequately covers what is returned (file_id and URL) and the output style. It does not mention markdown flavor support or size limits, but these are minor gaps given the tool's simplicity. The return value description is particularly helpful.
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 has 100% coverage with clear descriptions for both parameters (title and markdown). The tool description adds no extra semantic value beyond what the schema already provides, so the baseline score of 3 is appropriate.
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 ('Render') and resource ('Markdown') to a specific output ('PDF'), and clarifies the output style ('clean, print-styled'). This clearly distinguishes it from siblings like render_html_to_pdf and url_to_pdf by input type, so an agent can select it correctly without opening 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 implies the tool is for Markdown input, but does not explicitly state when to use it versus alternatives (e.g., render_html_to_pdf or url_to_pdf). No exclusions or preferred contexts are given, though the purpose itself is unambiguous enough to infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Combine 2+ PDFs into one, in order.
| Name | Required | Description | Default |
|---|---|---|---|
| pdfs | Yes | 2+ PDF sources. Each: A file_id from a prior tool result, or a base64-encoded PDF. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the core behavior (combining into one, in order) but does not disclose potential error conditions, file size limits, or whether inputs are modified.
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 extremely concise and free of fluff, conveying the necessary information in a single short sentence.
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?
The description is adequate for this simple tool. It doesn't specify the output format or return value, but for a merge operation that is typically a PDF file, the intent is clear. No output schema is provided, so the description needn't detail it.
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 schema provides a thorough description of the 'pdfs' parameter, including the minimum count (2) and the accepted formats (file_id or base64). The description reinforces this with '2+ PDFs'.
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 clearly states the verb (combine), the resource (PDFs), and the scope (2+), distinguishing it from sibling tools like split_pdf or rotate_pdf.
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 when to use it (merging PDFs) but does not explicitly mention alternatives or when not to use it. The intent is clear enough for the intended use case.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List a PDF's form fields (name, type, value, options) as JSON.
| Name | Required | Description | Default |
|---|---|---|---|
| Yes | A file_id from a prior tool result, or a base64-encoded PDF. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of disclosing behavioral traits. It does not mention whether the operation is read-only, any side effects, error handling, or limitations (e.g., unsupported PDFs). The name suggests read-only, but it is not explicitly stated.
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, concise sentence with no redundant words. It front-loads the action and clearly specifies the output, making it easy to parse.
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?
The description is complete for this simple tool: it fully explains the input parameter and describes the output format (JSON with name, type, value, options). No additional context is necessary for an agent to use it correctly.
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 for the 'pdf' parameter is thorough, explaining both accepted formats (a file_id from a prior tool result or a base64-encoded PDF) and providing context on provenance. This adds significant meaning beyond the string type in the 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 clearly states the tool's function with a specific verb 'List' and a specific resource 'PDF's form fields', and specifies the output format as JSON. This distinguishes it from sibling tools like extract_pdf_text and fill_pdf_form.
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 its usage by naming the exact task (listing form fields), but it does not explicitly state when to prefer this tool over alternatives or when not to use it. No direct comparison to sibling tools is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetch a public http/https URL and return its main content as clean Markdown — ideal for giving an agent readable web content for research or RAG. Private/internal hosts are blocked.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The http/https URL to read. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the transparency burden. It discloses output format and the host restriction, but does not mention potential limitations like size caps, redirects, or JavaScript rendering.
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 concise paragraph with no fluff, efficiently conveying purpose and key constraints.
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 single-parameter tool, the description is complete: it explains what it does, output format, and restrictions. It could mention error behavior or rate limits, but these are not essential for basic usage.
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 already describes the url parameter, and the description reinforces it by specifying 'public http/https URL', adding clarity about acceptable URL schemes and accessibility.
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?
Clearly states the action (fetch URL) and output (clean Markdown), distinguishing it from sibling tools like url_to_pdf and url_to_screenshot. Also specifies 'main content', which differentiates from raw HTML scraping.
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?
Provides a clear use case ('research or RAG') and a blocking constraint (private/internal hosts). Does not explicitly contrast with alternatives like scrape_page, but the stated purpose implies when to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Render a full HTML document to a PDF. External subresources are blocked for safety — inline images/fonts as data: URIs. Returns a file_id (for chaining) and a ~1h download URL.
| Name | Required | Description | Default |
|---|---|---|---|
| html | Yes | The complete HTML document to render. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the limitation of blocked external subresources and mentions the return values (file_id and download URL). Since there are no annotations, this description carries the full behavioral transparency burden and does so adequately, though it does not mention any potential side effects beyond the expected output.
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 concise, consisting of two clear sentences. It includes essential details (safety note, return values) without unnecessary fluff, making it efficient and well-structured.
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, the description is complete enough: it explains the input, the main behavior, safety limitation, and the output format. There is no output schema, but the description provides sufficient context about what the caller will receive.
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 sole parameter 'html' is fully described in the schema, and the tool description does not add extra context beyond the schema's description. Since schema coverage is 100%, the baseline of 3 is appropriate; no additional semantic value is provided.
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 clearly states the specific verb 'Render' and resource 'full HTML document to a PDF', making the tool's purpose unambiguous. It distinguishes itself from siblings by focusing on HTML input, which is a distinct action among the listed PDF tools.
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 provides a safety note about blocking external subresources, implicitly guiding when to use this tool (for inline/data: URIs) and when to consider alternatives (e.g., url_to_pdf for external resources). However, it does not explicitly state the comparison with siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Rotate every page of a PDF by 90, 180, or 270 degrees.
| Name | Required | Description | Default |
|---|---|---|---|
| Yes | A file_id from a prior tool result, or a base64-encoded PDF. | ||
| degrees | Yes | 90, 180, or 270. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of disclosing behavior beyond the action itself. It does not mention that the tool likely returns a new PDF file_id, whether it overwrites the input, or any side effects such as temporary file creation. The description only states what it does, not the complete behavioral contract.
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 well-formed sentence with no unnecessary words. It is front-loaded with the primary action and parameters, making it easy to scan and understand immediately.
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?
The description is sufficient for a simple tool with no output schema, covering the core action and allowed degrees. It lacks details about return values (e.g., whether it returns a file_id) and potential error conditions, but these are less critical given the tool's simplicity and the schema's completeness.
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 repeats the schema's parameter descriptions exactly ('pdf' and 'degrees') without adding any extra meaning. Since the schema already provides full descriptions for both parameters, the description contributes no additional semantic value, meeting the baseline for full schema coverage.
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 clearly specifies the verb ('Rotate'), the resource ('every page of a PDF'), and the exact allowed degrees (90, 180, or 270). It distinguishes this tool from sibling PDF operations like select_pages or split_pdf by indicating that all pages are affected.
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 guidance is provided on when to use this tool versus alternatives, such as select_pages for rotating a subset of pages or watermark_pdf for other modifications. The description does not state any prerequisites, recommended scenarios, or contrast with related tools, leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetch a public http/https URL and return its rendered HTML, the links on the page, and page metadata (title/description/OpenGraph/canonical/favicon) — in one render. For clean Markdown use read_url instead. Private/internal hosts are blocked.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The http/https URL to scrape. | |
| formats | No | Which representations to return (default: all three). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses that it renders the page and returns multiple representations in one render, and blocks private hosts. No annotations provided, so the description carries the burden; it does not mention rate limits or error behavior but covers key traits.
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 the main action and key differentiator front-loaded; no redundant wording.
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 no output schema, the description explains the return content (HTML, links, metadata with specific fields) and notes the single-call behavior, making it sufficient for an agent to understand expected outcomes.
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 describes both parameters (url required, formats optional with enum). The description adds context that all three formats are default and mentions the output types, but does not go beyond the schema's minimal descriptions.
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?
States a specific verb (fetch, return), resource (URL), and outputs (HTML, links, metadata), and distinguishes from read_url for 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?
Explicitly names the alternative for clean Markdown (read_url) and discloses the restriction on private/internal hosts.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Keep only the specified pages of a PDF.
| Name | Required | Description | Default |
|---|---|---|---|
| Yes | A file_id from a prior tool result, or a base64-encoded PDF. | ||
| pages | Yes | Pages to keep, e.g. '1,3,5-7'. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description alone must disclose behavior. It does not state whether a new PDF is returned, whether the original is modified, or what happens to unselected pages. The description lacks any transparency about side effects or return values.
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, short sentence that conveys the core function without extraneous detail. It is well-structured and easy to parse.
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 simplicity of the tool and lack of output schema, the description is adequate for basic understanding, but it omits details about the return format or potential errors. For a tool that likely outputs a PDF, knowing the output schema would be helpful but not strictly necessary.
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 schema covers both parameters with descriptions, and the 'pages' parameter includes an example format. However, the explanation is minimal and does not elaborate on edge cases like duplicate pages, ordering, or invalid ranges. Coverage is 100%, so baseline 3 applies.
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 clearly states the function: keeping only specified pages of a PDF. The verb 'Keep' is specific and the resource is a PDF. It is distinct from sibling tools like split_pdf or merge_pdfs by its name and action, though it does not explicitly differentiate them.
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 guidance is provided on when to use this tool versus alternatives. It does not mention that split_pdf creates multiple files or that merge_pdfs combines PDFs, leaving the selection criteria ambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Split a PDF into multiple PDFs — one per page by default, or by page ranges like '1-3;4-6'. Returns a file_id + URL per part.
| Name | Required | Description | Default |
|---|---|---|---|
| Yes | A file_id from a prior tool result, or a base64-encoded PDF. | ||
| ranges | No | e.g. '1-3;4-6'. Omit to split every page. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses the return format ('Returns a file_id + URL per part'), which is a useful behavioral trait. However, with zero annotations provided, the description carries the full burden and does not disclose whether the original PDF is modified, error behavior for invalid ranges, or any side effects. Partial disclosure only.
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 tight sentences with the core purpose front-loaded. Every sentence earns its place: the first states the action and default, the second gives the alternative syntax and return format. No fluff or redundancy.
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?
The tool is moderately complex (splitting with range syntax) and has neither annotations nor an output schema, so the description must carry more weight. It covers the core action, default behavior, range syntax, and return format, but omits differentiation from the similar select_pages sibling and does not address edge cases like invalid or overlapping ranges. Adequate but with clear gaps.
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% for both parameters (pdf and ranges), so the baseline is 3. The description largely repeats what the schema already states about ranges ('like 1-3;4-6' and 'Omit to split every page') and adds no new semantic detail such as 1-indexing, overlapping-range handling, or expected output count per range segment.
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?
States a specific verb (Split), resource (PDF), and behavior (multiple PDFs, per-page default or ranges). However, it does not distinguish split_pdf from the sibling tool select_pages, which also operates on page ranges and could be confused with this tool.
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?
Explains how to invoke the tool ('one per page by default, or by page ranges like 1-3;4-6'), but gives no guidance on when to use this tool versus alternatives such as select_pages, merge_pdfs, or extract_pdf_text. No explicit when-to-use or when-not-to-use guidance exists.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetch a public http/https URL and render the live page to a PDF. Returns a file_id (chainable into the PDF tools) and a ~1h download URL. Private/internal hosts are blocked.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The http/https URL to snapshot. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite having no annotations, the description carries full transparency: it discloses the private/internal host blocking constraint, the ~1h download URL expiration, the file_id return contract, and that it captures a live render. These are precisely the behaviors an agent needs to anticipate (auth restrictions, output lifetime, composability).
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?
Three sentences, each carrying distinct value: core purpose, output contract, and constraint. The main action is front-loaded, the parenthetical 'chainable into the PDF tools' adds composability context without bloat, and there is zero redundancy.
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 a single simple string parameter and no output schema, the description covers the essential contract thoroughly: input constraints, output format, and URL expiration. It omits edge-case behaviors like timeout or redirect handling, but for this complexity level the description is near-complete.
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 adds meaningful detail beyond the 100%-covered schema: it introduces the 'public' constraint not present in the schema's 'The http/https URL to snapshot' and specifies the return contract (file_id + download URL). The schema already covers http/https and the snapshot intent, so the added value is solid but not maximal.
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 specific verbs ('Fetch', 'render') and a clear resource ('public http/https URL' → 'PDF'), which distinguishes it from siblings like read_url (returns page content), url_to_screenshot (image output), and render_html_to_pdf (raw HTML input). The phrase 'live page' further differentiates it from file-based PDF tools.
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?
Implicit guidance is clear: 'public http/https URL' tells the agent this is for live web pages, not raw HTML or markdown (vs render_html_to_pdf, markdown_to_pdf) and not local files (vs merge_pdfs, split_pdf). Siblings are not explicitly named, but the constraints strongly imply when to choose this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetch a public http/https URL and capture a PNG screenshot. Set full_page for the entire scroll height. Returns a file_id and a ~1h download URL.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The http/https URL to capture. | |
| full_page | No | Capture the full scroll height (default: viewport). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of transparency. It discloses the output (file_id and ~1h download URL) and the input constraint (public URL), but it omits details about potential errors, timeout behavior, or side effects beyond the returned references. Still, the core behavior is well described.
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 concise—two sentences—and front-loaded with the primary action. It avoids unnecessary details and directly covers the main behavior and key option, with no wasted words.
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 simple tool, the description gives sufficient context: what input is expected, what output to expect, and the constraint on URL accessibility. It does not explain the file_id format, but that is likely not required for invocation, so the description is complete enough.
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?
Both parameters are explicitly described: url is the target to capture, and full_page controls scrolling. The description of full_page (default viewport) matches the schema's boolean type, providing clear semantics for the agent.
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 clearly states the action (fetch and capture), the resource (a public http/https URL), and the output (PNG screenshot). It is distinct from sibling tools like url_to_pdf (which produces PDF) and scrape_page (which extracts data), making its purpose unambiguous.
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 explains the core action and mentions the full_page option, but it does not explicitly contrast this tool with alternatives. An agent must infer when to choose a screenshot over a PDF or text extraction from the sibling list; the description alone does not provide explicit usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Stamp a diagonal grey text watermark across every page of a PDF.
| Name | Required | Description | Default |
|---|---|---|---|
| Yes | A file_id from a prior tool result, or a base64-encoded PDF. | ||
| text | Yes | The watermark text. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations present, the description carries the full burden of explaining side effects. It describes the stamping action but does not state whether the operation returns a new PDF, modifies the input, or affects the original file.
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 clear sentence with no unnecessary words. It directly conveys the core action and target.
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?
The description is adequate for a simple PDF operation, but it omits any mention of the output or return behavior. Since no output schema is provided, a brief note about the result would make it more complete.
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?
Both parameters are covered by schema descriptions: pdf and text. The description adds no extra semantic detail beyond the schema, but the schema itself is already sufficient for basic understanding.
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 the specific verb 'Stamp' and clearly identifies the resource and scope: a diagonal grey text watermark across every page of a PDF. This makes the tool's purpose immediately clear and distinguishable from sibling PDF tools.
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 states what the tool does but gives no explicit guidance about when to use it versus alternatives. It does not mention when watermarking is appropriate or when another PDF tool would be preferred.
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. Dates show when Glama detected each change.
extract_pdf_textfill_pdf_formimages_to_pdfmarkdown_to_pdfmerge_pdfsread_pdf_formread_urlrender_html_to_pdfrotate_pdfscrape_pageselect_pagessplit_pdfurl_to_pdfurl_to_screenshotwatermark_pdfClaiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
Open the connector listing, choose Claim ownership, and sign in to Glama.
Complete one verification method:
GitHub identity — fastest for official registry listings. For a namespace such as io.github.alice/server, link the matching GitHub user, then choose Claim with GitHub. An organization namespace such as io.github.acme/server also needs that organization to have installed the Glama AI GitHub App and approved its permissions, because GitHub discloses organization membership only to apps it has installed. Use HTTP or DNS when it has not.
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After verification, Glama sends a confirmation email and gives you access to listing details, thumbnails, health checks, and analytics. Keep the HTTP file or DNS record in place: Glama periodically checks it and ownership remains verified while the token is discoverable.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
}Claim tokens are opaque, stable, and bound to the signed-in Glama account. They contain no email address or other personal information. If Glama can no longer discover a verified HTTP or DNS token, it starts a seven-day grace period before removing claim-based access. Restore the same token during that period to keep ownership verified. Never publish an email address, Glama session token, GitHub token, or connector credential as ownership proof.
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For a connector linked to the official MCP Registry, registry updates continue to replace its name, description, and URL by default. After claiming, open Manage connector and enable Use Glama listing details as the source of truth if edits made on Glama should be preserved. Categories and thumbnails are always managed on Glama; registry linkage and technical connection settings continue to sync.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
To improve your MCP server's ranking:
Claim ownership of the server listing
Complete the server profile with an accurate description and thumbnail
Provide a test profile so Glama can connect to and evaluate the server
Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
Route real usage through the Glama Gateway; more recorded successful server uses also improve the ranking
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
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Free PDF tools for AI agents: merge, split, rotate, watermark, page numbers, metadata, flatten.
Generate and read PDFs for AI agents: a generate_pdf and a read_pdf tool, priced per document.
Read a URL as clean markdown, screenshot a website, url to PDF. Web access for agents, no signup.
Web data tools for AI agents: pages as markdown, search, maps, commerce, jobs, AI answers.
Add one secure layer between your agents and this server.
Most tools have clearly distinct purposes, such as extracting PDF text versus filling forms or rendering URLs to PDF versus screenshots. The only mild overlap is read_url and scrape_page, both fetching a URL, but their outputs are explicitly differentiated as clean Markdown versus raw HTML with metadata.
Names mostly follow a verb_noun pattern like extract_pdf_text, fill_pdf_form, and rotate_pdf. A few conversion tools use 'to' constructions (images_to_pdf, markdown_to_pdf, url_to_pdf) and some pluralize objects (merge_pdfs, select_pages), creating minor inconsistency but no real confusion.
With 15 tools, the set is at the upper edge of the ideal range and every tool serves a distinct, useful function within the PDF and URL processing domain. The count feels justified rather than excessive.
The PDF tooling covers creation from images and Markdown, text extraction, form filling and reading, merging, splitting, rotating, selecting pages, and watermarking. URL handling covers reading as Markdown, scraping raw HTML/metadata, generating PDFs, and taking screenshots, providing well-rounded coverage for the stated domain.
