Oviond

Audit report health

audit_report_health

Read-only

Audit a report or dashboard: list its connected data sources and automation state, and flag likely issues (no data sources connected, paused automations). Read-only.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`id`	Yes	Report ID to audit (from list_reports)

Output Schema

TableJSON Schema

Name	Required	Description	Default
`data`	No	The audit — the report, the datasources its client has connected, its automations and their state, and the issues found (no datasource connected, automations paused).
`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": {
+      "description": "The audit — the report, the datasources its client has connected, its automations and their state, and the issues found (no datasource connected, automations paused)."
+    },
+    "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

A4.3/5.0

Behavior4/5

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

Beyond the annotations (readOnlyHint=true, destructiveHint=false), the description discloses what the audit covers and what kinds of issues it flags. The explicit 'Read-only' statement reinforces the annotations without contradicting them, adding practical behavioral context.

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?

A single, front-loaded sentence that states the verb, resource, and expected output without filler. Every clause contributes meaningful information, making it easy for an agent to parse quickly.

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?

With one well-documented required parameter, a schema coverage of 100%, an output schema available, and annotations covering safety, the description fills the remaining behavioral gap—what the audit inspects and flags. Nothing essential for correct invocation is missing.

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 description coverage is 100%; the schema already documents the id parameter and its provenance ('from list_reports'). The description adds no new parameter semantics beyond the schema, so the baseline score 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 uses a specific verb ('Audit') with a clear resource ('report or dashboard') and enumerates the concrete outputs: connected data sources, automation state, and flagged issues. This distinguishes it from related sibling tools like get_report or list_automations, which retrieve data but do not aggregate health signals.

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 conveys the intended use case: check a report/dashboard for likely problems such as missing data sources or paused automations. It does not explicitly name alternative tools or state when not to use it, but the context is clear enough for an agent to route to this tool over simple getters or listers.

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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