smart_test

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

With no annotations, the description carries full burden. It discloses that the tool shows only failures by default, includes fields like expected/received and truncated stack, and auto-detects test frameworks. However, it does not mention whether the command execution is read-only or could have 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 extremely concise: two sentences covering purpose, default behavior, and auto-detection. Every word adds value, and the most important information is front-loaded.

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?

For a 5-parameter tool with no output schema and no annotations, the description provides solid context: default output, auto-detection, and structured format hints. It could be more explicit about return structure, but is adequate for an agent to invoke correctly in most cases.

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 all parameters described. The description adds minimal extra parameter context beyond the schema (e.g., default show_passes behavior is implied). As a result, it meets the baseline but does not significantly enhance understanding.

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 executes a test command and returns structured, actionable output. It specifies default behavior (shows only failures) and lists detected test frameworks, distinguishing it from sibling tools like filtered_grep or smart_git which have different purposes.

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 implies usage for running test commands, but does not explicitly state when to use this tool versus alternatives like filtered_shell for arbitrary commands or when to prefer other tools. The context from sibling names helps but the description lacks explicit usage guidance.

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