test_selection_suggestion

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

With no annotations, the description carries the full burden. It hints at a read-only suggestion (no mutation implied) but does not disclose key traits like whether a project must be registered, if results are deterministic, or if it modifies any state. The description is adequate but not explicit about side effects.

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 a single, well-structured sentence that immediately conveys the tool's purpose. Every word is meaningful, with no superfluous content.

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?

Despite having an output schema, the description does not explain what the tool returns (e.g., list of test case IDs, scores). It omits prerequisites like whether the project must be analyzed first, and lacks any usage examples or edge-case handling, leaving the agent under-informed for a 3-parameter tool.

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 coverage is 100% with clear descriptions for all three parameters. The description adds no additional semantics beyond 'changed file paths' and 'limit', so it does not enhance parameter understanding significantly; baseline 3 is appropriate.

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 'Preset query: suggest smallest high-signal test subset to rerun after change' clearly states the action (suggest) and resource (test subset), with specific qualifiers ('smallest high-signal', 'rerun after change'), distinguishing it from sibling tools like 'analyze_project' or 'impact_analysis'.

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?

No guidance is given on when to use this tool versus alternatives (e.g., 'impact_analysis' or 'search_test_case'). The description does not mention prerequisites or exclusions, leaving the agent to infer the appropriate context without support.

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