get_hot_keys

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

No annotations are provided, so the description carries full burden. It discloses that data is from persisted storage, uses LFU or idletime, and that signalType indicates mode. This is sufficient for a read-only monitoring tool, though no auth or rate limits are mentioned.

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 two sentences long, with the purpose front-loaded. Every sentence adds value without redundancy. No wasted words.

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?

Despite no output schema and no annotations, the description covers the tool's purpose, mechanism, and usage. It lacks details on output fields beyond signalType, but for a monitoring tool, this is adequate.

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 documents all parameters. The description adds minimal extra meaning beyond what the schema provides (e.g., 'top keys' implies limit but schema already describes limit). Baseline 3 applies.

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 gets hot key tracking data, specifies the resource and action. It also explains the underlying mechanism (LFU or idletime), which distinguishes it from siblings like cache_health or get_memory.

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 explicitly states use cases: 'find cache-busting keys, uneven access patterns, or keys that dominate throughput.' It provides clear context for when to use the tool, though it doesn't mention when not to use it or directly compare with alternatives.

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