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update_dashboard

Replace the definition behind an existing dashboard link. The id and the link stay the same, so anyone holding the link sees the new dashboard.

Validates and grounds the new definition exactly as mint_dashboard does: if it would render broken the stored dashboard is left untouched. Prefer this over minting a second link for a dashboard the user already has. Call get_dashboard first to fetch the current definition rather than rebuilding one from memory.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesThe id of the dashboard to replace, as returned by mint_dashboard.
rangeNoOptional range override for the link, <n>m|h|d, e.g. 24h.
refreshNoOptional refresh interval override in ms; 0 disables.
definitionJsonYesThe full replacement definition as a JSON string.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added
  2. Removed
  3. Added

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden. It discloses validation and grounding behavior, the atomicity guarantee (if it would render broken, the stored dashboard is left untouched), and the side effect that anyone holding the link sees the new dashboard. It does not cover permissions or rollback beyond the broken-render case, but the core mutation behavior is transparent.

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 compact and front-loaded with the primary action and side effect. Each sentence earns its place: behavior, safety guarantee, usage preference, and pre-call guidance are all included without redundancy.

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?

For a mutation tool with no output schema and no annotations, the description covers the important operational context: what gets replaced, who is affected, how validation works, and the recommended pre-step. It could also mention what happens on success or how errors besides broken rendering are reported, but it is largely complete.

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%, so all four parameters are already documented in the schema. The description adds context about fetching the current definition first and replacing it, but does not add material meaning beyond the schema for individual parameters, warranting the baseline score.

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 clearly states the verb ('Replace') and the resource ('the definition behind an existing dashboard link'), and explains the key invariant that the id and link stay the same. This differentiates it from minting a new dashboard and from get_dashboard/delete_dashboard siblings.

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?

It explicitly says to prefer this over minting a second link when the user already has a dashboard, and instructs the agent to call get_dashboard first rather than rebuilding from memory. This gives concrete when-to-use and when-not-to-use guidance.

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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