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iampopovich

Allure TestOps MCP

by iampopovich

get_test_result_retries

Retrieve retry history for a test result to detect flaky tests by comparing status across previous attempts.

Instructions

Get the retry history for a test result. Returns the list of previous attempts for the same test in the same launch. Key tool for flaky test detection: if a test failed on attempt 1 but passed on attempt 2, it is a flaky test, not a real failure. Check status across retries to assess reliability.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesTest result ID. Must be a number (integer), not a string.
pageNoPage number, 0-based.
sizeNoPage size.
Behavior3/5

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

No annotations are provided, so the description bears the burden of behavioral context. It discloses that the tool returns a list of previous attempts, but does not mention pagination behavior (despite page/size parameters), rate limits, or any side effects. The added context is useful but incomplete.

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 extremely concise with only two sentences, the first stating the purpose and the second providing use guidance. Every word adds value, and the key information is front-loaded.

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?

Given no output schema and no annotations, the description could be more complete. It does not describe the structure of each retry attempt or how to interpret the list. While the flaky test scenario adds some context, the overall completeness is moderate for a tool of this complexity.

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 coverage is 100% with detailed parameter descriptions (e.g., id must be a number). The description does not add extra meaning beyond the schema, so a baseline score of 3 is appropriate.

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 the tool gets retry history for a test result, and distinguishes it by focusing on previous attempts for the same test in the same launch. This specificity differentiates it from siblings like get_test_result and get_test_result_history.

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

Usage Guidelines4/5

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

The description explicitly positions the tool for flaky test detection with a concrete scenario (failing on attempt 1, passing on attempt 2). It advises assessing reliability across retries, providing clear use guidance. However, it does not explicitly state when not to use it or mention alternatives, missing full exclusion criteria.

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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