adb_regression_check

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

Since no annotations are provided, the description bears the full burden. It discloses that it flags regressions with specific percentage thresholds and that thresholds are configurable. However, it does not mention potential side effects, error conditions (e.g., missing baseline), or return format.

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, consisting of two sentences. The first sentence states the purpose, and the second provides details. No wasted words, and it is front-loaded with the core action.

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 tool with 5 parameters and no output schema, the description sufficiently covers the core functionality and key thresholds. It lacks details on return values or error handling, but the purpose and inputs are clear enough for an agent to use 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 coverage is 100%, so the schema already details all parameters. The description adds value by explaining the context of thresholds and defaults, reinforcing what the schema provides. Baseline is 3, and the description neither significantly adds nor detracts.

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 it compares current performance against a saved baseline and flags regressions in memory, CPU, and jank. However, it does not explicitly distinguish from sibling tools like 'adb_regression_baseline' or 'adb_regression_history', but the verb 'compare' and specific metrics make the purpose clear.

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 when a baseline exists and regressions need checking, but it does not provide explicit when-to-use or when-not-to-use guidance. No mention of alternatives or prerequisite conditions.

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