extract_pdf
Structured PDF extraction from base64-encoded PDF bytes. $0.05/call via x402.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| doc_type | No | auto | |
| file_base64 | Yes |
Agent Utility API
TDQS
B3.4/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, placing the transparency burden on the description. It discloses the cost per call via x402, which is useful, but it does not describe output format, error handling, file size limits, or required permissions. The phrase 'structured PDF extraction' gives a hint but remains vague.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, two short sentences, with no filler. The key information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given its simplicity, the description covers the core purpose but lacks detail on return structure, error cases, and the role of doc_type. With no output schema or annotations, more completeness would be expected.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides two parameters, and description coverage is 0%. The description does add meaning for file_base64 by specifying base64-encoded PDF bytes, but doc_type is entirely undocumented, leaving the second parameter unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool's function: extracting structured data from PDFs given base64 input. The phrase 'structured PDF extraction' distinguishes it from any sibling tools, none of which handle PDFs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives is provided. However, since sibling tools serve unrelated purposes (lookups, crypto, transcription, web reading), usage is implied, but no exclusions or prerequisites are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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TDQS
A3.7/5.0
Disambiguation5/5
Each tool has a clearly distinct purpose: company lookup, crypto price, email verification, PDF extraction, KDP data, social profile lookup, YouTube transcription, and web reading. No two tools overlap in their primary function, so an agent can easily select the right one.
Naming Consistency3/5
Names follow a snake_case convention but mix verb-object (extract_pdf, transcribe_youtube) and object-verb (company_lookup, email_verify, web_read) orders. Also, crypto_price is noun-noun, breaking the verb pattern. The inconsistency is noticeable but names remain readable.
Tool Count5/5
With 8 tools, the server is well-scoped for a general-purpose utility API. Each tool adds a distinct capability without redundancy or bloat, fitting comfortably within the optimal 3-15 tool range.
Completeness4/5
The set covers common agent needs like web reading, PDF extraction, email verification, and social/company analysis. However, some obvious utilities like image processing or file conversion are absent, representing minor gaps but not severe dead ends.