aggregate_test_cases_by_feature

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behaviors: it searches across multiple text fields, uses case-insensitive partial matching, groups results by Root Suite and Feature Suite while avoiding duplicates, and offers multiple output formats. This covers search scope, matching logic, result organization, and output options, though it doesn't mention rate limits, permissions, or error handling.

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 efficiently structured with four sentences that each add value: the core purpose, search scope and matching logic, result grouping method, and output formats. It uses emojis and formatting for readability without wasting space, and every sentence contributes essential information.

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 tool's moderate complexity (search across multiple fields with hierarchical grouping), no annotations, and no output schema, the description does well to cover purpose, behavior, and output options. It could be more complete by mentioning what the different output formats contain or any limitations, but it provides sufficient context for an agent to understand when and how to use this tool effectively.

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?

Schema description coverage is 100%, so the schema already documents all 5 parameters thoroughly. The description adds some context by mentioning 'case-insensitive, partial match' for the feature_keyword parameter and listing output formats, but doesn't provide additional semantic meaning beyond what's in the schema descriptions. This meets the baseline for high schema coverage.

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 specific action ('Find ALL test cases related to a specific feature'), the resource ('test cases'), and scope ('across the project'). It distinguishes from siblings by specifying it searches across multiple fields (title, description, preconditions, test steps) and groups results hierarchically, unlike tools like 'get_test_case_by_title' or 'get_test_cases_by_suite_smart' which have narrower scopes.

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 provides clear context for when to use this tool: when searching for test cases related to a feature across the entire project with case-insensitive partial matching. It doesn't explicitly state when not to use it or name specific alternatives, but the context is sufficient to differentiate from siblings that filter by suite, key, or other criteria.

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