timps_visual_regression_detective

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

With no annotations, the description carries the safety/behavior transparency burden. It does convey a non-mutating-sounding 'diff and surface' behavior and hints at an explanatory output, but it does not explicitly say whether baselines or files are modified, whether external services are contacted, or what format the root-cause hints take.

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 sentence that front-loads the action and scope, then states the expected outcome. There is no filler, repetition, or unnecessary qualifier.

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 two-parameter tool with no output schema and no annotations, the description provides a solid overview but still leaves important context unstated: the exact shape/format of the report, what happens when a baseline is missing, and whether this is a read-only operation. It is adequate for basic selection but not fully self-contained.

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?

The schema already describes both parameters at 100% coverage, so the description does not need to document them. The description adds no extra semantics about how 'request' should be structured or how 'language' affects the diff, leaving it at the baseline score.

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 identifies the resource ('design tokens / Storybook / screenshot baselines') and the specific action ('Diff ... and surface unintended visual changes with root-cause hints'). This distinguishes it from sibling detective/review tools like timps_flaky_test_detective or timps_storybook_story_generator.

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 use case is implied: it should be used when you need visual regression checks or diff-based visual change detection. However, there is no explicit 'use when...' statement, no exclusions, and no direct comparison to sibling tools that might handle related visual or testing concerns.

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