dataverse_list_connection_references

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, destructiveHint. The description goes beyond by explaining that empty connectionid means runtime failure, and it details the returned fields and their meaning. No contradiction with annotations.

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?

Concise and well-structured: purpose sentence first, then list of returned fields, followed by practical filtering advice. Every sentence adds value with no redundancy.

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 (multiple parameters, filtering, and output), the description covers essential usage scenarios and field meanings. The presence of an output schema further reduces the need to document return structure in the description.

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%, so the description must compensate. It adds meaningful guidance for using filter, statecode, and connector_id parameters, and interprets the output's connection_id field. It does not detail the 'top' or 'dataverse_url' parameters, but those are straightforward or have defaults.

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 lists connection references and specifies the exact fields returned (connectionreferenceid, logical name, etc.). It distinguishes itself from sibling tools like dataverse_get_connection_reference by indicating it returns multiple records.

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?

Provides concrete guidance on when to use each filter parameter (connector_id, statecode) and explains the significance of the connection_id field for runtime failures. Does not explicitly mention when not to use the tool or alternative tools, but the use cases are clearly outlined.

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