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qase-tms

Qase MCP Server

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by qase-tms

qql_search

Read-onlyIdempotent

Search and filter Qase entities across projects using QQL query expressions for precise data retrieval.

Instructions

Search entities using Qase Query Language (QQL) with powerful filtering and cross-project queries

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of results to return (default: 10, max: 100)
queryYesQQL query expression. Examples: - entity = "case" and project = "DEMO" and status = "Actual" - entity = "defect" and severity = "blocker" and status = "open" - entity = "result" and status = "failed" and ended >= now("-7d") - entity = "run" and milestone ~ "Sprint 12" See QQL documentation for full syntax and examples.
offsetNoNumber of results to skip for pagination

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
totalYesTotal matching entities
entitiesYesMatching entities
Behavior3/5

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

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds feature context ('powerful filtering and cross-project queries') but does not disclose additional behavioral traits such as pagination behavior, rate limits, or query validation. No contradiction with annotations.

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, front-loaded sentence with no wasted words. It immediately communicates the verb and resource, making it highly efficient and well-structured.

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

Completeness4/5

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

Given the complexity of QQL, the description is minimal but sufficient because the schema provides detailed query syntax examples and the output schema is present. It adds the key differentiator of cross-project search. Mentioning qql_help for further syntax guidance would improve completeness, but the existing structured data compensates.

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

Parameters3/5

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

The input schema provides 100% coverage with detailed examples for the query parameter and clear limit/offset descriptions. The description's mention of 'powerful filtering' adds little beyond the schema's rich examples, so it does not significantly enhance parameter understanding.

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

Purpose5/5

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

The description clearly states a specific action ('Search') on a resource ('entities') using a distinct method ('Qase Query Language'), and highlights 'cross-project queries' which distinguishes it from sibling tools like qase_get and qql_help.

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 description implies this is the appropriate tool for complex, filtered QQL searches but does not explicitly state when to use it over alternatives like qase_get or when to consult qql_help. No exclusions or alternative tool references are provided.

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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