get_cluster_efficiency

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

No annotations provided, but the description explains the 4 dimensions scoring, weightage, and behavior without metrics-server. It does not specify if it's read-only or triggers changes, but the detailed behavior offsets the lack of annotations. However, it could mention if it requires permissions or cluster access.

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 well-structured, starting with the main output, then breaking down dimensions, followed by a note on metrics-server, and ending with examples. It is front-loaded with key information, though slightly verbose in the dimension breakdown.

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 and lack of output schema, the description provides a good overview of scoring dimensions and behavior. However, it doesn't specify return format, recommendation details, or prerequisites (e.g., cluster connectivity). It is adequate but not fully complete.

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 only parameter is 'context' (optional, string or null) with 0% schema coverage in the description. The description does not explain what 'context' does or how to use it, leaving agents uncertain. This is a significant gap despite low parameter count.

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 provides a Kubernetes cluster efficiency score (0-100) with letter grade, per-namespace breakdown, and prioritised recommendations. It distinguishes itself from sibling tools like get_databricks_cluster_efficiency and get_kubernetes_costs by specifying 'Kubernetes' and 'efficiency' vs costs.

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 notes that it works without metrics-server, using request fill-ratio, which gives usage context. However, it does not explicitly state when not to use this tool or mention alternatives like get_databricks_cluster_efficiency. The examples help, but usage guidance is implied rather than explicit.

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