list_spark_applications

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

With no annotations, the description carries full burden. It states the return type (dict with applications list) but omits details like pagination behavior, required permissions, error conditions, or whether the list is complete. The limit parameter hint is helpful but insufficient for full transparency.

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, with a clear structure separating purpose, arguments, and returns. No redundant sentences, though the 'Args:' format is slightly verbose. It could be shorter, but remains efficient.

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 lack of annotations and no output schema provided, the description partially compensates by mentioning the return value. However, it does not cover pagination, error handling, or prerequisites. For a list endpoint, this is a moderate gap.

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%, so the description effectively documents all three parameters. It provides examples for state, and for limit it gives a range and a recommendation. engine_id is described as 'Spark engine identifier', which adds minimal but sufficient context beyond the schema type.

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 lists Spark applications on a Spark engine. This distinguishes it from siblings like get_spark_application_status (for a single app) and submit_spark_application. However, it could be more specific about the scope (e.g., whether it returns all applications or those belonging to the caller).

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 a clear use case (listing applications) and includes a recommendation for limit to avoid token exhaustion. However, it does not explicitly state when not to use this tool or differentiate it from alternatives like get_spark_application_status.

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