Oviond

Update goal widget

update_goal_widget

Point a Goal widget at a saved goal. Ids come from list_goals. The goal carries its own metric query, target and comparison, so nothing else is needed; the gauge is re-fetched in the background.

Input Schema

TableJSON Schema

Name	Required	Description
`id`	Yes	Widget ID (from list_widgets).
`name`	No	Display name. Omit to show the goal's own name.
`goal_id`	Yes	Goal id (from list_goals).

Output Schema

TableJSON Schema

Name	Required	Description	Default
`data`	No	The widget as saved, now pointed at that goal. The gauge is re-fetching in the background — read it with get_widget_data.
`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 widget as saved, now pointed at that goal. The gauge is re-fetching in the background — read it with get_widget_data.",
+      "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

A4.7/5.0

Behavior5/5

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

Beyond the annotations, the description reveals useful behavior: the goal owns its metric configuration and the gauge is re-fetched in the background. This sets agent expectations about side effects and the scope of the update better than the annotations alone.

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, front-loaded sentences with no filler. Each sentence contributes either to the primary purpose, ID sourcing, or behavioral expectations.

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?

For a moderate-complexity update tool, the description covers purpose, ID provenance, the absence of extra configuration, and background refresh behavior. An output schema exists, so return-value explanation is not required.

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. The description adds extra meaning by explaining why only a widget id and goal id are needed ('the goal carries its own metric query, target and comparison'), which helps the agent avoid providing unnecessary 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?

States a specific verb and resource: 'Point a Goal widget at a saved goal.' This clearly distinguishes the tool from update_goal (which edits the goal itself) and other widget-update siblings.

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?

Provides clear context: the operation targets an existing Goal widget, IDs come from list_goals, and no metric query/target/comparison fields are needed. It does not explicitly name alternative tools or state when not to use it, so it stops short of a 5.

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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