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suniljavadi

Data Engineering MCP Server

by suniljavadi

search_incidents

Search historical synthetic incidents by query to retrieve relevant records for investigating data engineering failures and ETL issues.

Instructions

Search historical synthetic incidents.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.4/5.0
Behavior2/5

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

Annotations are absent, so the description carries the full burden of behavioral disclosure. It reveals only that incidents are 'historical synthetic' data but does not state whether the operation is read-only, how matching works, or how results are ordered; the output schema may cover return shape, but behavior beyond that is undisclosed.

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

Conciseness3/5

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

The sentence is extremely concise and front-loads the resource, with no filler words. However, it is under-specified for an AI caller: it omits usage guidance and parameter semantics, so the brevity comes at the cost of completeness.

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?

For a simple 2-parameter search tool with an output schema, the description is not completely inadequate because it names the resource. Yet it leaves usage, matching behavior, and parameter semantics unspecified, forcing the agent to guess how to construct a valid query.

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 does not compensate. It does not explain what the required 'query' means, whether 'limit' caps the result count, or any format expectations. The only available parameter information comes from type/default fields in the schema.

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 uses a specific verb ('Search') and a clear resource ('historical synthetic incidents'), which distinguishes it from the job-, database-, and documentation-focused siblings at a high level. It does not explicitly contrast itself with search_documentation, but the resource noun alone largely disambiguates.

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 given about when to use this tool versus alternatives, what scenarios it fits, or when it should not be used. The agent must infer domain fit solely from the resource name, with no exclusion criteria or alternative routing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.