get_cluster_deployments

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

No annotations are provided, so the description fully informs about behavior. It notes that the tool 'Polls the cluster via the VibOps gateway (up to 20s),' alerting the agent to potential latency and live connection. This is valuable transparency beyond a simple getter.

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 concise: a single opening sentence defining the tool, followed by a behavior note and usage guidance. The Args section is structured cleanly. Every sentence adds value; no 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 a tool with 2 params and no output schema, the description covers the return type (replica counts, pod health, resource usage), the polling mechanism, and param usage. It is adequate; missing details like pagination or error cases are minor given the simplicity.

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 0%, but the description adds meaningful parameter descriptions: 'cluster_name' is tied to 'list_clusters' output, and 'namespace' is explained as restricting results to a single namespace. This provides context the schema alone lacks.

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 explicitly states it returns 'live Kubernetes deployment status for a cluster, including replica counts, pod health, and resource usage.' The verb 'return' and specific resource 'deployment status' make the purpose clear. It distinguishes from siblings like 'run_kubectl' and 'scale_deployment' by focusing on read-only status.

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 advises calling it 'when investigating deployment health, replica counts, or pod failures.' This provides clear context for usage. No explicit when-not or alternative tools are mentioned, but the guidance is sufficient for decision-making.

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