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Describe Dashboards

describe_dashboards
Read-onlyIdempotent

The complete guide to composing a Fixter dashboard: the definition format, panel kinds and their roles, how to choose chart forms from the measure, grid layout rules, units, environment scoping, and what mint_dashboard validates. Call this once before composing your first dashboard in a conversation.

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / $schema
      Added value: +"https://json-schema.org/draft/2020-12/schema"
    • removedInput schema / additionalProperties
      Removed value: -false
  2. Added
  3. Removed
  4. Added

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and closed-world, so the safety profile is covered without the text. The description adds real value by disclosing the exact subject matter and the 'call once' lifecycle, but says nothing about the returned form (prose vs. structured document) or size, which matters for a zero-argument guide tool an agent must consume.

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?

Two sentences with no filler: the purpose is front-loaded, the topic enumeration follows, and the call instruction is last where an agent will read it before acting. The content list is long but every item is distinct information the guide actually contains, so nothing is padding.

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?

With zero parameters, no output schema, and rich annotations, the description carries the burden of telling the agent what it will learn – and it does so item by item, which functions as a table of contents for the return value. The only gap is that it does not characterize the response format, a minor omission for a static guide tool.

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?

The tool takes no parameters, so there is no parameter semantics to explain and the baseline of 4 applies. The description correctly avoids inventing or implying any arguments.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Names a specific verb and resource (a complete guide to composing a Fixter dashboard) and enumerates its exact contents: definition format, panel kinds, chart-form selection, grid layout, units, environment scoping, and mint_dashboard validation. That enumeration makes it unmistakably a documentation tool rather than a reader like get_dashboard or a writer like mint_dashboard, though it never explicitly contrasts itself with those 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?

The closing sentence gives explicit, actionable timing: 'Call this once before composing your first dashboard in a conversation' – it states both when (before composing) and the cadence (once), which implicitly forbids repeated calls. It stops short of naming alternatives for the reuse case, so it is strong but not fully complete on when-not.

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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