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MarkIvor

DataSearcher MCP

by MarkIvor

create_public_dashboard

Generate a standalone HTML dashboard with interactive filters to share data insights directly from your database queries.

Instructions

Создаёт дашборд — standalone HTML с интерактивными фильтрами.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleYes
descriptionNo

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

B3.1/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral disclosure burden. It does reveal that the output is a standalone HTML artifact with interactive filters, which is useful, but it omits side effects, the public exposure implications, access considerations, and what the returned result contains.

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 a single, tightly worded sentence with no filler. It front-loads the core action and then adds the most decision-relevant detail, the standalone HTML format with interactive filters.

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

Completeness3/5

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

For a simple creation tool with an output schema and self-explanatory parameters, the description is minimally sufficient. However, the missing clarification of the 'public' aspect and the lack of differentiation from other dashboard-creation siblings mean an agent could select or invoke it incorrectly in a larger toolset.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate, but it does not mention the title or description parameters at all. The schema itself shows types and defaults, so this is not a complete failure, but the description adds no parameter-level meaning.

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?

The description states a clear action and resource: it creates a dashboard, and further specifies the output as standalone HTML with interactive filters. However, it does not distinguish this from the sibling build_dashboard or clarify what 'public' means in the tool name.

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?

There is no guidance on when to use this tool versus alternatives like build_dashboard, visualize_data, or data_story. No contexts, exclusions, or selection criteria are provided, leaving the agent to infer usage from the name alone.

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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