get_cluster_resource_balance

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

With no annotations provided, the description carries the full burden and does well by disclosing key behavioral traits: it explains the tool's focus on 'Request vs Usage gaps', diagnostic purposes, and returns a 'Markdown table showing CPU/Memory Requests vs Usage per node'. It doesn't mention rate limits or auth needs, but covers output format and use cases adequately.

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 appropriately sized and front-loaded, starting with the core purpose, followed by a bulleted 'Why Essential' section for context, and ending with return details. Every sentence earns its place by providing clear, non-redundant information without unnecessary elaboration.

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 (diagnostic analysis), no annotations, 0 parameters, and an output schema (implied by 'Has output schema: true'), the description is complete enough. It explains the purpose, usage scenarios, and return format, compensating well for the lack of annotations and leveraging the output schema for return values.

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 input schema has 0 parameters with 100% coverage, so the baseline is 4. The description adds no parameter information, which is appropriate since no parameters exist, maintaining the baseline without penalty.

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's purpose with specific verbs ('Analyze cluster resource balance') and resources ('Request vs Usage gaps'), distinguishing it from siblings like 'get_cluster_storage_report' or 'get_gpu_utilization' by focusing on resource allocation diagnostics rather than storage, GPU, or pod-specific metrics.

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 when to use this tool through the 'Why Essential' section, listing specific scenarios like 'Scheduling bottleneck diagnosis', 'Resource fragmentation detection', and 'Cost efficiency'. It implicitly distinguishes from siblings by not covering GPU health, storage, or pod logs, providing clear context for its application.

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