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MarkIvor

DataSearcher MCP

by MarkIvor

search_knowledge

Search a knowledge base for table metadata, column descriptions, metrics, and examples using combined full-text and semantic search to locate relevant data definitions.

Instructions

Поиск по базе знаний: метаданные таблиц, описания колонок, метрики, примеры (ТЗ 8). Комбинирует полнотекстовый и семантический поиск.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
top_kNo

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

B3.2/5.0
Behavior3/5

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

With no annotations, the description carries the burden of disclosing behavior. It does reveal a meaningful behavioral trait: it combines full-text and semantic search. However, it does not mention result ordering, whether it only reads data, any limitations on query structure, or how `top_k` affects behavior.

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

Conciseness4/5

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

Two concise sentences with no filler. The scope is listed first, followed by a useful behavioral detail. The cryptic parenthetical '(ТЗ 8)' adds little for an agent, but it does not significantly harm clarity.

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?

The tool has an output schema, so return values are covered elsewhere. The description gives the core purpose and hybrid-search behavior, but it lacks parameter-level guidance and explicit routing versus sibling tools. It is adequate for a simple search tool but has clear gaps in usage recommendations.

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 for the two parameters. It does not explain what `query` should contain or how `top_k` controls result count. The parameter names are somewhat self-explanatory, but the description adds no meaning beyond the raw schema fields.

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 specific action and resource: searching the knowledge base for table metadata, column descriptions, metrics, and examples. It also adds a differentiator by noting it combines full-text and semantic search, which helps separate it from the sibling `semantic_search`. It does not explicitly name sibling tools, but the scope is much clearer than a generic 'search' statement.

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

Usage Guidelines3/5

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

The usage context is implied: use this tool to find knowledge-base content such as metadata and column descriptions. The hybrid-search note implies it is appropriate when both full-text and semantic matching are needed, but it does not state when to prefer `semantic_search`, `get_schema`, or other siblings, nor does it give any exclusions.

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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