Plutus

get_dashboard

Read-onlyIdempotent

Fetch one org-shared dashboard's full layout — its placed widgets, custom metrics and custom charts, and their grid positions. A widgets entry references a preset catalog_id (see list_dashboard_widget_catalog); customMetrics/customCharts carry their own full config inline. Call this before set_dashboard_widgets if you want to keep some of what's already there rather than replacing the whole set — that tool always replaces everything.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`dashboard_id`	Yes	A shared dashboard id from list_dashboards

TDQS

A4.3/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds useful structural context (widgets reference catalog_id; customMetrics/customCharts are inline) and warns about set_dashboard_widgets' replace-all behavior, but does not disclose additional behavioral traits like pagination, authorization, or error characteristics. This is typical baseline value beyond annotations.

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 three sentences with no filler. It front-loads the core function, then adds essential structural detail, then closes with a practical usage warning. Every sentence earns its place and the content is easy to scan.

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 single-parameter, read-only, idempotent fetch operation, this description is complete. It identifies what is returned, how widget references are resolved, and how the tool relates to set_dashboard_widgets. No output schema exists, but the description covers the return contents sufficiently for an agent to know what to expect.

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?

The single parameter dashboard_id is fully documented in the schema as 'A shared dashboard id from list_dashboards', giving 100% schema coverage. The description reinforces that the dashboard is org-shared but adds no new parameter-level meaning. Baseline 3 per the rubric 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 ('Fetch') and a specific resource ('one org-shared dashboard's full layout'), then enumerates the exact contents: placed widgets, custom metrics, custom charts, and grid positions. This clearly distinguishes it from sibling list_tools like list_dashboards or list_dashboard_widget_catalog.

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 the agent when to call this tool: before set_dashboard_widgets when preservation of existing items is desired, because that tool always replaces everything. This is concrete, actionable routing guidance that names the alternative and the condition for choosing this tool.

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

A3.9/5.0

Disambiguation4/5

Tools are organized by resource (budgets, alerts, anomalies, dashboards, cost tags, recommendations), so most are clearly separable. The cost-tag cluster and the dimension/facet listers are the places where an agent could misselect by name, though descriptions resolve the ambiguity.

Naming Consistency5/5

All tools use snake_case verb_noun names with a clear convention: get_ fetches specific items, list_ enumerates collections, and query_ runs time-bucketed or analytical queries. The pattern holds across all 29 tools with no camelCase or mixed verb styles.

Tool Count2/5

29 tools is well past the typical 3–15 sweet spot and even past the 16–25 heavy band, so the surface feels sprawling despite having few duplicates. Each tool maps to a distinct endpoint, but the sheer number makes it a heavy set for an agent to select from.

Completeness2/5

The read-side is strong: costs, usage, tags, budgets, alerts, anomalies, dashboards, recommendations, and data health are all queryable. However, the surface is almost entirely read-only, and descriptions reference absent tools like create_budget, create_alert_subscription, create_dashboard, set_dashboard_widgets, and delete_dashboard, creating dead ends. That is a significant gap for a cost-management platform.

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