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Kamy

by dev.kamy

Extract document (Kamy Ingest)

extract_document

Extract structured data from a PDF (invoice, receipt, contract, ID document, or any form). Returns the parsed JSON plus a public verify URL that proves the extraction matches the source. Use this when an agent needs to read an inbound document and act on it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
templateYesPredefined template id. invoice/receipt for AP and POS docs, contract for legal agreements, id_document for passports/IDs, generic_form for anything else.
source_urlNoPublic URL to a PDF (preferred). One of source_url or source_base64 is required.
source_base64NoBase64-encoded PDF bytes. Use when the source isn't publicly fetchable.

TDQS

A3.5/5.0
Behavior1/5

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

The description directly contradicts the annotations. readOnlyHint is false, yet the description frames the tool as a read-only operation ('read an inbound document', 'Extract'), implying no side effects. This is a serious inconsistency that could mislead an agent about the tool's side effects.

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 two sentences long, front-loaded with the action and object, and every sentence serves a purpose: stating the function and providing usage guidance plus return value details. There is no wasted text.

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?

The description explains return values (parsed JSON and verify URL) which is necessary since there is no output schema. It also covers typical input types. However, it omits any mention of side effects or persistence that the 'Ingest' title implies, and the read-only framing contradicts annotations, leaving key context incomplete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already provides 100% parameter coverage with descriptions for all three parameters. The description adds no extra parameter-level semantics beyond what the schema offers, so the baseline of 3 is appropriate.

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 opens with a specific verb+resource: 'Extract structured data from a PDF' and enumerates common document types (invoice, receipt, contract, ID document, any form). This clearly distinguishes it from sibling tools like render_pdf or verify_pdf_signature, which serve different purposes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit usage context: 'Use this when an agent needs to read an inbound document and act on it.' This tells the agent when to choose this tool, though it doesn't explicitly mention when not to use it or name alternatives. The guidance is clear but lacks exclusions.

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

A4.4/5.0
Disambiguation5/5

Each tool targets a distinct action or resource with minimal ambiguity. For example, `render_pdf`, `render_docx`, `render_xlsx`, and `pptx` are clearly different output formats, while `merge_pdfs`, `split_pdf`, and `edit_pdf` target different PDF operations. The signature tools (`create_signature_request`, `get_signature_request`, etc.) are also clearly separated by lifecycle stage. No two tools appear to do the same thing.

Naming Consistency5/5

Tool names follow a highly consistent `verb_noun` pattern throughout, such as `create_signature_request`, `get_signature_request`, `list_signature_requests`, and `remind_signature`. This pattern is applied uniformly across all major domains (render, signature, template, webhook, trace), making the API predictable and easy for an agent to navigate.

Tool Count4/5

With 59 tools, this is a large surface area, but it is justified by the breadth of functionality: document rendering in multiple formats, e-signatures, template management, webhooks, scheduling, and a crypto/audit trail. While large, each tool has a distinct purpose, and the count feels appropriate for the scope of a comprehensive document automation API. A surface this large risks being overwhelming, but the internal organization is logical.

Completeness5/5

The tool surface is remarkably complete, covering the full lifecycle for multiple domains. For e-signatures, there are tools for CRUD (requests, templates), sending (individual, bulk, envelope), monitoring (get, list), reminders, and certificates. For documents, it covers creation, conversion, editing, merging, splitting, and verification. The inclusion of utility tools like `get_started`, `validate_payload`, and the audit trail tools further solidifies this as a well-considered, production-ready API surface.

Resources