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MarkIvor

DataSearcher MCP

by MarkIvor

auto_insights

Retrieve top five data insights with accompanying charts from any table in a single call. Provide a table name and optional focus to automate analysis.

Instructions

Авто-инсайты: топ-5 находок с графиками 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

D1.3/5.0
Behavior1/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only gives a high-level promise and does not state whether the tool is read-only, requires a connected table, handles empty tables, or has any side effects. This is a significant transparency gap.

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 description is short (one sentence) but is under-specified rather than concise. It front-loads the tool name and gives no operational detail, so the sentence is not efficiently informative. The brevity does not serve the agent's needs.

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

Completeness1/5

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

Given the tool likely performs complex analysis and returns charts, the description is far from complete. It lacks any explanation of prerequisites, return format, parameter usage, or output schema details, making it inadequate for an agent to call correctly. The presence of an output schema does not compensate for the missing behavioral and parameter context.

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?

The schema has zero description coverage for its two parameters (table_name and focus), and the description does not explain their roles or required formats. An agent cannot infer what table_name refers to or how to use the optional focus parameter, so the description adds no value beyond the schema.

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 states it returns 'top-5 findings with charts in one call,' giving a basic idea, but it does not specify what kind of data, what constitutes a 'finding,' or how it differs from other analysis tools like smart_summary or detect_anomalies. The verb is implicit and the resource is vague, so it only partially clarifies purpose.

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

Usage Guidelines1/5

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

No mention of when to use this tool versus alternatives, no conditions or exclusions. The description provides zero guidance on selection criteria, leaving the agent to guess based on the tool 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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