dataverse_list_solution_components

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds that it returns human-readable type names, which is useful behavioral context, but does not elaborate on pagination, default top value, or any rate limits. With annotations carrying the burden, this is adequate but not exceptional.

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 extremely concise: two sentences. The first sentence states the primary action, and the second provides actionable filtering guidance. Every sentence earns its place with zero wasted words. Structure is optimal 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 has 4 parameters, clear annotations, and an output schema, the description covers the essential purpose and filtering. It mentions human-readable type names and provides key type codes. It could briefly mention the default top value or that results are paginated, but these are already in the schema. Overall, it is complete enough for smooth invocation.

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 descriptions already cover all parameters (top, solution_id, dataverse_url, component_type) with full detail. The description only restates some type codes for component_type and adds the concept of human-readable names. Since schema coverage is effectively high, the description adds marginal value, warranting a baseline 3.

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 'List components within a Dataverse solution', which is a specific verb+resource combination. It distinguishes from sibling tools like dataverse_list_solutions by focusing on components within a solution, and adds value by mentioning human-readable type names.

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 context for using the tool ('List components within a Dataverse solution') and gives explicit filtering instructions for component_type with common codes. However, it does not mention when not to use this tool versus alternatives (e.g., using specific getters for individual components) or provide any exclusion criteria.

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