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Render a batch of PDFs

render_batch

Render up to 100 documents in a single blocking call, each from its own template, HTML or URL, and get every result back in one response. Choose this over calling render_pdf in a loop whenever you have more than a couple of documents — it is one round trip, one quota reservation and one rate-limit charge. It does block: items render sequentially inside a 300-second budget, so expect to wait, and reach for render_async instead when you cannot. Returns { results: [...] } in request order, where each entry is either a finished render or an { error: { code, message } } — a partial batch is normal and successful items are still yours. The whole batch's quota is reserved up front, so a batch that would cross the monthly quota is rejected in full with 402 and nothing is rendered; call get_account first if you are near the limit. Items that would overrun the time budget come back as SERVICE_UNAVAILABLE having been neither rendered nor billed — retry just those in a smaller batch.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsYes1-100 documents to render, in order. Results come back in this same order.

TDQS

A4.8/5.0
Behavior5/5

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

The annotations are minimal (readOnlyHint=false, etc.), so the description carries the full burden. It richly discloses behavioral traits: the tool blocks and renders sequentially within a 300-second budget, partial batches are normal with per-item errors, quota is reserved upfront leading to full rejection on quota exceedance, and time-budget overruns yield SERVICE_UNAVAILABLE without billing. This far exceeds what annotations provide.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is approximately 150 words across 6 sentences, which is slightly long but each sentence adds unique value. It is front-loaded with the core purpose and usage guidance, then layers in behavioral details. Could be slightly more concise by removing the example response structure, but overall earns its length.

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?

Given the tool's complexity (batch processing, partial failures, quota, timeout), the description is remarkably complete. There is no output schema, so the description compensates by explaining the return format and error semantics. It covers all major dimensions: what it does, when to use vs. alternatives, behavioral traits, and how errors/quota/timing work. No gaps identified.

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?

Schema coverage is 100%, so the baseline is 3. However, the description adds meaningful context about the batch-level behavior (e.g., partial errors, quota reservation, time-budget overrun handling) that enriches understanding beyond parameter-level descriptions. It explains the response structure and error semantics, which is not in the schema. The slight deduction is because it doesn't elaborate on each parameter individually, but the aggregate value is significant.

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 states the tool's purpose: 'Render up to 100 documents in a single blocking call, each from its own template, HTML or URL, and get every result back in one response.' It uses a specific verb ('render') and resource ('batch of PDFs'), and implicitly distinguishes itself from siblings like render_pdf and render_async.

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 tells when to use this tool over alternatives: 'Choose this over calling render_pdf in a loop whenever you have more than a couple of documents' and 'reach for render_async instead when you cannot [block].' It also provides when-not-to-use guidance (when blocking is unacceptable). This is a textbook example of usage guidelines.

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.