Brainiall Documents

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already cover read-only, idempotent, and non-destructive behavior. The description adds the return format (dictionary with status='healthy' or an actionable error object) and reinforces that no input is needed. This adds useful context beyond the annotations without contradiction.

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 and front-loaded: first sentence states the purpose, second gives usage guidance, third clarifies no input, and return info is presented. Each sentence adds value with no 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?

For a zero-parameter health check tool, the description covers what it does, when to use it, and what it returns. It even specifies the error format. Combined with the safety annotations, nothing essential is missing 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?

With 0 parameters and 100% schema coverage, the baseline is 4. The description clarifies that no document input is required, which aligns with the empty schema. No further parameter explanation is necessary.

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 action ('Check whether document conversion and extraction are available') and clarifies the resource. It also explicitly distinguishes from siblings by noting that no document input is required, which differentiates it from the extraction 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?

Provides explicit usage scenarios: 'before a workflow' and 'when another document tool reports a temporary availability problem'. This gives clear context and implies when not to use it (i.e., for actual extraction), and the note about no input further clarifies its role.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already cover read-only, idempotent, and non-destructive behavior. The description adds genuinely useful behavioral context: PDF input is rejected, the output is a dictionary with request metadata/fields/text, and failures return an actionable error object. This goes beyond what annotations alone provide.

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 compact and front-loaded: purpose first, usage guidance second, output behavior last. Every sentence earns its place, and no information is repeated from the schema unnecessarily.

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 three-parameter image extraction tool with high schema coverage and clear sibling routing, the description is nearly complete. The only minor gap is the lack of auth/rate-limit context, but the annotations and return-shape summary cover the essential operational guidance.

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 description coverage is 100%, so the schema already explains url, doc_type, and image_base64. The description reinforces relevant use cases like invoices, receipts, and forms, but it does not add substantial new parameter-level meaning 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?

States a specific verb and resource: 'Extract structured fields and full text from a document image.' It also distinguishes itself from pdf_to_markdown by emphasizing 'named fields rather than Markdown,' making the tool's role clear relative to its siblings.

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 says when to use it: for invoices, receipts, forms, and PNG/JPEG images when named fields are needed. It also gives a clear exclusion: PDF input is intentionally rejected and pdf_to_markdown should be used instead. This is strong alternative routing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds value by stating the return behavior: 'Markdown text on success, or an actionable error object on failure.' This clarifies outcomes without contradicting the annotations or omitting major behavioral traits for a read-only conversion tool.

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 compact and well-organized: a front-loaded purpose statement, a brief usage paragraph with input constraints, and a distinct Returns line. There is no filler or repetition of schema details, and every sentence contributes to the agent's understanding.

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 tool's purpose, input sourcing, optional page range, and return behavior. Since there is no output schema, the explicit mention of 'Markdown text' and 'actionable error object' helps set expectations. It does not discuss size limits or authentication, but for a simple read-only converter with fully described parameters and safety annotations, the definition is adequately 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?

Schema description coverage is 100%, and the schema already explains each parameter, including the mutual-exclusivity of url and pdf_base64. The description's extra notes—'Supply exactly one source' and 'optional page range is useful for large documents'—reinforce but do not materially add to the schema. A baseline of 3 is appropriate since the schema carries the parameter documentation burden.

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 opening sentence, 'Convert a PDF into readable Markdown for analysis and retrieval,' provides a specific verb, resource, and output format. It also lists the content types preserved (text, headings, tables, structure), which clarifies scope. However, it does not explicitly name or distinguish itself from the sibling tools check_document_service and extract_document_fields, so it falls short of full sibling differentiation.

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 tells the agent exactly when to use it: 'Use this when an agent needs the text, headings, tables, and document structure from a PDF.' It also gives practical input guidance ('Supply exactly one source') and notes the page_range option for large documents. It does not provide explicit when-not-to-use cases or point to alternative tools, so it stops at clear context rather than full exclusion guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.