Lumino

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

No annotations are provided, so the description carries the full burden. It discloses behavioral traits by listing what it identifies (e.g., pending pods, OOMKilled containers) and the return structure, but it does not cover aspects like authentication needs, rate limits, or whether it performs read-only operations. The description adds value by specifying the tool's focus and output, but gaps remain in operational 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 appropriately sized and front-loaded, starting with the core purpose followed by details in bullet points and a clear return structure. Every sentence earns its place by adding specific information without redundancy, making it efficient and well-structured for quick understanding.

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), lack of annotations, and presence of an output schema, the description is complete enough. It explains what the tool checks, the single parameter's role, and the return keys, which aligns well with the output schema detailing the response structure. No significant gaps are present for effective use.

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 description adds meaning beyond the input schema by explaining that the 'namespace' parameter is for 'Kubernetes namespace to inspect,' which clarifies its purpose. With 0% schema description coverage and only one parameter, the description compensates well by providing context, though it could include more details like format or examples. The baseline is high due to low parameter count and effective compensation.

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 a specific verb ('Check') and resource ('resource constraints in a namespace'), and it distinguishes itself from siblings by focusing on pipeline-impacting constraints rather than general analysis or listing functions. It explicitly lists what it identifies (e.g., pending pods, OOMKilled containers), making the scope precise and differentiated.

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 provides clear context for when to use this tool ('that may impact pipelines'), but it does not explicitly state when not to use it or name alternatives among the sibling tools. While it implies usage for pipeline-related issues, it lacks explicit exclusions or comparisons to tools like 'analyze_failed_pipeline' or 'conservative_namespace_overview'.

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