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MarkIvor

DataSearcher MCP

by MarkIvor

build_dashboard

Build a dashboard of 4-6 key charts from a database table in a single call. Provide a table name and get visual insights for data analysis.

Instructions

Набор из 4-6 ключевых графиков одним вызовом.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
focusNo
table_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.0

TDQS

D1.9/5.0
Behavior2/5

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

There are no annotations, so the description carries the full burden of behavioral disclosure. It adds only a small behavioral fact (a batch of 4-6 charts in one call) but omits whether this is read-only, what the response contains, whether it mutates state, and how failures or partial results are handled.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The text is short, but brevity here is under-specification rather than effective conciseness. The only informative content is a count range and 'one call,' which is not enough to make the description useful.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return-value details are not strictly required. However, the description still lacks the selection criteria for the charts, the role of the focus parameter, and any differentiation from closely related siblings, leaving the tool incomplete for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description mentions neither table_name nor focus. An agent cannot infer what table_name refers to, what focus controls, or how the choice of default '' affects the dashboard, so the description does nothing to compensate for the schema gap.

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

Purpose2/5

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

The description is a noun phrase ('A set of 4-6 key charts in one call') with no explicit verb or resource, so it only weakly indicates that the tool builds or returns a dashboard. It also does not explain what makes charts 'key,' which prevents an agent from distinguishing it from sibling tools like visualize_data or create_public_dashboard.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided about when to use build_dashboard versus calling individual chart tools, visualize_data, or create_public_dashboard. The phrase 'in one call' implies a convenience/batching purpose, but there is no explicit context, precondition, or alternative.

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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