query_lmk_rate

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

With no annotations provided, the description carries the transparency burden. It explains the metric's meaning, its user-perceived scope, the inclusion of distinctUsers, daily-only aggregation, and how rolling averages can be requested. It does not cover potential response shape or permissions, but for a query tool this is reasonable context.

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 three sentences long, front-loaded with the primary purpose, and every sentence provides useful information: metric definition, sibling-tool relationship, and aggregation guidance. No filler 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?

For an 8-parameter query tool with no output schema and no annotations, the description covers the essential context: metric semantics, related tools, aggregation constraints, and rolling-average options. It could mention pagination or response structure, but the schema already documents parameters well and the description compensates where it matters most.

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 baseline is 3. The description adds genuine value by naming the default metrics (userPerceivedLmkRate, distinctUsers), suggesting valid metric values for rolling averages, and reinforcing that aggregation_period only supports DAILY. This goes beyond the schema's generic array descriptions.

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 opens with a specific verb and resource: 'Query the low-memory-kill rate' and precisely defines the core metric userPerceivedLmkRate. It clearly distinguishes this tool from sibling stability tools by contrasting LMK with crash and ANR metrics.

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 clear usage context: read it alongside query_crash_rate and query_anr_rate because LMK is a stability failure that is not reported as a crash. It also gives concrete guidance about requesting rolling average metrics, though it does not explicitly enumerate when not to use the tool.

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