get_capacity_overview

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds valuable behavioral context beyond that: capacity_remaining_pct exists only at group level and values are None while capacity analytics warm up. This helps the agent set expectations about the data returned.

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, opening with a [READ] marker and a single concise sentence that captures the core output. It then gives a brief caveat and usage guidance, followed by an Args block. Every sentence earns its place with no filler.

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, the description names the returned fields and their semantics, notes the warming-up edge case, and points to sibling tools for specific follow-ups. For a simple read tool with two parameters, this is complete enough for an agent to select and invoke it correctly.

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?

Input schema has 0% description coverage, but the description's Args section compensates fully. It explains cluster_id is the cluster resource UUID from list_resources and target is an Aria target name from config with default when omitted. This adds meaning the schema 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 clearly states the tool returns a capacity overview for a cluster, including group-level remaining-capacity percentage, per-dimension absolute remaining capacity, and projected days-until-full. It names specific metrics and explicitly differentiates from sibling tools get_remaining_capacity and get_time_remaining, leaving no ambiguity about scope.

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 says 'Start here when assessing overall cluster capacity health' and then gives explicit alternatives: 'for absolute headroom values use get_remaining_capacity, and for just the exhaustion projections use get_time_remaining.' This is excellent when-to-use guidance and distinguishes from siblings.

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