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Anythink-MCP

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Dashboards: widget preview

dashboards_widget_preview
Read-only

Preview the data a widget would draw without saving it. Test a saved chart by id or try list, markdown, and view configs before adding them to a dashboard.

Instructions

Show the data a widget would draw, without saving it. Works for a saved chart, given its id, and for list, materialised view, markdown and other widgets, given their config. Use it to see what a saved chart shows now, or to try a widget before adding it with dashboards_add_chart or dashboards_update; use dashboards_data for widgets already on a dashboard. Returns JSON.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rowsNoMost rows or points to show (default 20)
typeNoWidget type: chart, materialised_view, list, quick_action, markdown, media or getting_started
chartNoChart to preview (for a chart widget)
configNoThe widget's settings as JSON, e.g. {"entityName":"orders","limit":5} for a list

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.2.37

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already establish readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds useful context beyond that: it is a dry-run that does not save, and it returns JSON. It stops short of detailing response shape or any auth/limit behavior, but with annotations carrying the safety profile this is solidly above baseline.

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 tight sentences, front-loaded with the core action and scope. Every clause carries routing information or a behavioral constraint; nothing is redundant.

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 multi-mode preview tool with readOnly annotations and no output schema, the description covers the supported widget types, the two invocation modes, the routing to add/update/data siblings, and the return format. An agent has everything needed to call it correctly.

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 goes further by mapping the two usage modes to parameters: a saved chart is previewed by id ('chart'), while list, materialised view and markdown widgets are previewed via their config, which clarifies how 'chart' and 'config' relate.

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 ('Show') and resource ('the data a widget would draw') and immediately clarifies the non-persistent preview scope. It names the sibling tools it is not (dashboards_data, dashboards_add_chart, dashboards_update), so an agent can disambiguate without opening any schema.

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?

Explicit when-to-use: to see what a saved chart shows now, or to try a widget before persisting it. It names the alternative 'dashboards_data' for widgets already on a dashboard and ties add/update flows to dashboards_add_chart and dashboards_update. Nothing is left to inference.

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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