get_cascade_metrics

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

With no annotations, the description carries the full burden. 'Get live metrics' implies a read-only, non-destructive operation and it discloses the data categories returned, but it omits any mention of permissions, rate limits, caching behavior, or potential side effects. It provides minimal but useful behavioral 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 a single, well-structured sentence that front-loads the core action ('Get live metrics') and then succinctly lists the specific metrics. There is 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?

Given the simplicity (no parameters, no output schema) and the description's enumeration of returned metrics, it is mostly complete. It does not specify the exact format or units of the metrics, but for a straightforward read-only metrics endpoint this is sufficient for an agent to understand what it provides.

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?

The tool takes zero parameters, so the baseline of 4 applies. There are no parameter semantics to document, and the description does not need to compensate for schema gaps.

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 states a specific verb ('Get') and resource ('live metrics') and enumerates the exact quantities returned (tokens saved locally on the RTX 5090, offload percentage, biasing state). It clearly distinguishes the tool's purpose, though it does not explicitly differentiate from sibling query_local_5090.

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?

No guidance is given on when to use this tool versus alternatives like query_local_5090 or cascade_llm. The usage is implied (retrieve metrics), but there are no conditions, prerequisites, or exclusions stated.

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