allure_get_test_case

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

Annotations already indicate read-only, non-destructive, idempotent behavior. The description adds valuable detail: it returns a dict with specific keys, including 'steps' with 'depth' marker, and clarifies that steps are empty when 'include_scenario' is false. This goes beyond annotations without contradicting them.

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

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

The description is well-structured: a clear first sentence stating purpose, a contrast with a sibling, and a concise return format. It is appropriately sized—every sentence adds value without unnecessary fluff.

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

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

Given the presence of an output schema, the description complements it well by listing the dictionary keys and explaining the step structure. It covers the essential aspects of the tool's behavior and return value comprehensively.

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

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

Input schema covers both parameters with descriptions. The description adds context about the structure of steps and the effect of 'include_scenario' (an extra call), which is not in the schema. Since schema coverage is 100%, baseline is 3, but the extra context justifies a 4.

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

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

The description clearly states the tool 'Get one test case's full detail' and lists specific fields (status, layer, tags, steps). It explicitly distinguishes from the sibling 'allure_list_test_cases' which returns summaries, making it easy for an agent to select the correct tool.

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

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

The description explicitly contrasts with 'allure_list_test_cases' and says 'Use it to read or review the actual content of a test case.' It also explains the effect of 'include_scenario', providing clear when-to-use and when-not-to-use guidance.

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