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iampopovich

Allure TestOps MCP

by iampopovich

search_test_cases

Search test cases with AQL queries, applying filters on fields like name, status, tag, and custom fields.

Instructions

Search test cases by AQL query.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectIdNoProject ID. Must be a number (integer), not a string.
projectNameNoProject name (alternative to projectId).
rqlYesAQL (Allure Query Language) filter expression. Operators: = != ~= (contains) > < >= <= in [...] and or not. IMPORTANT: 'not in' is written as 'not field in [...]', NOT 'field not in [...]'. Test case fields: id, name, tag, issue, role["R"], member, cf["F"], cfv, layer, status, workflow, testPlan, automation (boolean), muted, mutedDate, createdDate, createdBy, lastModifiedDate, lastModifiedBy. Dates use 13-digit Unix ms timestamps. Examples: name ~= "login" | automation = true | automation = false | status = "Active" | tag in ["smoke", "regression"] | not tag in ["nightly"] | cf["Epic"] = "Auth" | name ~= "checkout" and muted = false | (createdBy = "a" or createdBy = "b") and automation = true
pageNoPage number, 0-based. Must be a number (integer), not a string.
sizeNoPage size. Must be a number (integer), not a string.
sortNo
Behavior2/5

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

With no annotations, the description carries full burden for behavioral traits. It only says 'Search test cases by AQL query' and omits crucial details: no mention of being read-only, no disclosure of permissions, rate limits, pagination behavior, or side effects. The minimal description leaves significant gaps.

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 extremely concise (5 words) but at the expense of necessary detail. For a complex tool with an AQL query language, it should provide more structure or examples. This is under-specification, not efficient conciseness.

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?

Despite the rich schema for rql, the tool description is incomplete. It does not explain return values, pagination behavior, or how to effectively use the query language. Given the complexity (6 params, no output schema), the description is insufficient for an agent to confidently invoke the tool.

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?

Schema description coverage is high (83%), and the description adds no additional meaning beyond what the schema provides. The rql parameter has a very detailed schema description, so the tool description's lack of parameter info is acceptable but does not enhance 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 'Search test cases by AQL query', which specifies the verb (search), resource (test cases), and method (AQL query). It effectively differentiates from siblings like list_test_cases (simple list) and other search tools (search_launches, search_test_results).

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 that this tool is for complex filtering via AQL, but it does not explicitly state when to use it versus alternatives like list_test_cases or other search tools. No exclusions or when-not-to-use guidance is 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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