ctt_item_analysis

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does mention 'with warnings,' but gives no detail about what triggers warnings, how missing responses are handled, or what assumptions are checked. The description is too thin to fully describe the tool's runtime behavior.

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 a single efficient sentence with no wasted words, and the primary action is front-loaded. It is appropriately concise, though it sacrifices useful detail that other dimensions require.

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?

The tool has no annotations and zero parameter description coverage, so the description must carry more weight. It omits input-format expectations, warning semantics, and any guidance for choosing this analysis over the sibling tools. With an output schema present, return values may be covered, but the input and decision context are not.

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 description coverage is 0%, and the description provides no information about the input parameters. It does not explain the expected responses matrix, the optional item_names field, or the format required for correct invocation, so it adds no value beyond the raw schema.

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 uses a specific verb ('Compute') and lists concrete outputs: item summaries, item-rest correlations, raw alpha, and SEM. This clearly identifies the tool as a classical test theory item analysis, though it does not explicitly differentiate it from sibling tools like correlation_matrix or rasch_model.

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?

There is no guidance on when to use this tool versus alternatives such as descriptive_statistics, correlation_matrix, or rasch_model. The intended use is only implied by the tool name and the listed outputs, with no exclusions, prerequisites, or decision context provided.

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