Oviond

Generate PDF

generate_pdf

Queue a PDF render of a multi-page report. Returns a job_id — poll get_pdf_status until it completes, then download the URL. Dashboards have no pages to paginate and are rejected.

Input Schema

TableJSON Schema

Name	Required	Description
`format`	Yes	Page size: A4 or Letter
`client_id`	Yes	Client the report belongs to (from list_clients)
`report_id`	Yes	Multi-page report to render (from list_reports, type REPORT). A dashboard is rejected.
`orientation`	Yes	portrait or landscape

Output Schema

TableJSON Schema

Name	Required	Description	Default
`data`	No	The queued job — job_id to poll with get_pdf_status, and its initial status.
`success`	Yes	True when the call succeeded. A failure comes back as an error result instead.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 18, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": false,
+  "properties": {
+    "data": {
+      "additionalProperties": {},
+      "description": "The queued job — job_id to poll with get_pdf_status, and its initial status.",
+      "type": "object"
+    },
+    "success": {
+      "description": "True when the call succeeded. A failure comes back as an error result instead.",
+      "type": "boolean"
+    }
+  },
+  "required": [
+    "success"
+  ],
+  "type": "object"
+}

First observedSep 18, 2026

TDQS

A4.4/5.0

Behavior4/5

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

Annotations already mark this as non-read-only and non-destructive. The description adds meaningful context beyond annotations: the operation is asynchronous ('Queue'), returns a job_id, requires polling, and rejects dashboards. This gives the agent a solid mental model of the lifecycle. It doesn't cover auth, rate limits, or error handling other than the dashboard rejection, but the core behavioral traits are disclosed.

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?

Three short sentences with no filler. The first sentence states the action, the second explains the follow-up workflow, and the third gives the critical exclusion. Every sentence earns its place; the most important information is front-loaded.

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

Completeness4/5

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

The description, combined with a rich schema and an output schema, covers the action, the async polling flow, and an important failure case. It omits other potential failure modes (e.g., invalid report_id, backend errors) and does not mention any rate limits, but those are not essential for a basic invocation. The core end-to-end usage is complete; a small gap remains around additional error scenarios.

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?

Schema coverage is 100%: all four parameters have descriptive text, including report_id's note that dashboards are rejected. The description reinforces the multi-page report requirement and dashboard rejection, but does not add any semantic detail beyond the schema. Baseline 3 is appropriate when the schema fully documents parameters.

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: 'Queue a PDF render of a multi-page report.' It also immediately distinguishes the tool from its complementary sibling get_pdf_status by naming the polling flow wedre. The explicit rejection of dashboards further clarifies the exact input type. No ambiguity remains about what this tool does.

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 gives direct procedural guidance: 'poll get_pdf_status until it completes, then download the URL.' It also states an explicit when-not-to-use condition ('Dashboards have no pages to paginate and are rejected'). While no alternate PDF-generation tool exists, the workflow and exclusion are crystal clear.

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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