Trace focused package/activity per display (blocking)

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

Description discloses blocking behavior and artifact writing for large sample sets, which are key behavioral traits not covered by annotations. However, it does not mention permissions, prerequisites, or potential side effects, slightly limiting full transparency.

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?

Description is three concise sentences with front-loaded purpose, no redundant wording, and each sentence adds distinct value.

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 the tool's complexity (6 parameters, blocking nature), the description omits return format, error conditions, and prerequisites. The existence of an output schema only partially compensates.

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 only 17%, and the description adds no parameter-specific information. Essential parameters like durationMs, maxSamples, and includeAllSamples lack meaningful explanation beyond the schema defaults.

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?

Description clearly states the tool performs a blocking trace of focused package/activity/taskId per display for a fixed duration. It explicitly distinguishes from the start/stop variant, making the purpose unambiguous.

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?

Explicitly recommends preferring mobile_focus_trace_start/stop for interleaved scenarios, providing clear when-to-use guidance. Also notes the artifact behavior for large samples.

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