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Extract from a render

extract_from_render
Read-only

Read the text or the form fields back out of a document this account already rendered, without uploading anything. Pass type='text' (the default) for per-page text plus a joined fullText string, or type='fields' for the PDF's AcroForm field names, types and current values — the latter is how you discover what edit_pdf can fill in. Choose extract_document instead when the PDF came from outside Kamy or when you need AI-structured JSON against a schema; this tool is a plain mechanical read of an existing render, spends no render quota and no extraction credits. The render must have status 'success' or the call returns 409 RENDER_NOT_READY.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNo'text' (default) returns { pages: [{ page, text }], fullText, pageCount }. 'fields' returns the AcroForm fields as { name, type, value }.
render_idYesRender id (UUID) as returned by render_pdf, render_async/get_job, or list_renders.

TDQS

A4.9/5.0
Behavior5/5

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

Beyond the readOnlyHint=true annotation, the description adds concrete behavioral traits: 'without uploading anything', 'spends no render quota and no extraction credits', and the specific error return '409 RENDER_NOT_READY' when the render isn't successful. It also details the two output modes, which is rich contextual information.

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 a single, dense paragraph. Every sentence earns its place: purpose, modes, alternative guidance, resource traits, and error condition. It is front-loaded with the core purpose and avoids redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having no output schema, the description fully explains return shapes (per-page text plus fullText; fields as name/type/value), error behavior, resource usage, and the distinction from sibling tools. For a tool with only 2 parameters, this is complete and self-sufficient.

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

Parameters4/5

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

The schema already describes both parameters fully (100% coverage). The description adds extra meaning by explaining that type='fields' reveals what edit_pdf can fill in, and by detailing the return structures for both types. This enriches parameter semantics beyond the schema's descriptive text.

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 'Read' and clearly states the resource: 'the text or the form fields back out of a document this account already rendered.' It distinguishes from sibling extract_document by explicitly saying when to use extract_document instead, making the purpose unambiguous.

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

Usage Guidelines5/5

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

The description explicitly provides when-to-use: 'Choose extract_document instead when the PDF came from outside Kamy or when you need AI-structured JSON against a schema.' It also clarifies the mechanical read nature, resource usage (no quota/credits), and the precondition that the render must have status 'success'.

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

A4.2/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose with detailed descriptions that differentiate similar tools (e.g., render_pdf vs render_async vs render_batch, create_signature_request vs create_envelope). No two tools overlap in a way that would cause confusion.

Naming Consistency5/5

All tool names follow a consistent lower_snake_case verb_noun pattern (e.g., attest_artifact, convert_document, list_renders). No mixing of conventions or ambiguous verb choices.

Tool Count4/5

47 tools is high but reflects the broad scope of the platform (document generation, signing, auditing, scheduling, webhooks, verification). Some informational tools could be merged, but the count is still reasonable for the domain.

Completeness3/5

The tool set covers the core document lifecycle well but has notable gaps: no tool to delete renders, no tool to void/cancel signature requests, and no CRUD for templates (only list and schema). The inability to pause schedules via MCP is also a gap.

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