design.regression_test

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

Annotations already declare readOnlyHint and idempotentHint, so the description does not need to restate those. It adds information about the comparison algorithm (Pixelmatch) and output format (diff image, change percentage). No contradictions, but no additional behavioral details beyond annotations.

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 concise, with two sentences that front-load purpose and output. Every sentence adds value: the first explains what the tool does and returns, the second specifies where the baseline comes from. No fluff or redundancy.

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 no output schema, the description adequately explains return values (diff image, change percentage, pass/fail). It also covers parameter usage, prerequisite (baseline snapshot source), and algorithm. The tool is fully described for an agent to invoke correctly.

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% for all 5 parameters. The description adds context that baseline_snapshot_id comes from design.track_changes, but overall does not significantly enhance meaning beyond the parameter descriptions in the schema. Baseline score 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 clearly states the tool performs pixel-level comparison between a baseline snapshot and current web page using Pixelmatch, and returns threshold-based pass/fail, diff image, and change percentage. It distinguishes from siblings by specifying the use of snapshots from design.track_changes, making it unique among similar tools.

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 a clear prerequisite: use snapshots from design.track_changes snapshot action as baseline. It implies the use case for regression testing. However, it does not explicitly state when not to use this tool or compare with alternatives like design.compare.

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