get_conversations

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true. The description adds that it returns conversation history with inputs, outputs, and metadata, but does not disclose additional behavioral traits such as rate limits, authorization needs, or pagination behavior. It adds modest context beyond the 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?

The description consists of two concise sentences. The first sentence states the core functionality, and the second provides a typical use case. There is no unnecessary information, and it is front-loaded with the essential action.

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 description adequately explains the return value (conversation history including inputs, outputs, and metadata) given the absence of an output schema. However, it omits details about pagination, ordering, or limits for the list endpoint. Still, for a low-complexity tool (2 simple parameters, no nested objects), the description is sufficient.

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 has 100% description coverage for both parameters (projectId and contactIds). The description does not add extra meaning beyond what the schema already provides, such as format constraints or defaults. The baseline score of 3 is appropriate since the schema is self-sufficient.

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 verb 'gets', the resource 'conversations for specific contacts', and the scope 'in a Cognigy.AI project'. It also specifies what is returned (conversation history including inputs, outputs, and metadata) and a use case ('analyze user interactions'). This distinguishes it from sibling tools like 'get_conversation' (singular) and 'get_transcript'.

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 says 'Use this to analyze user interactions', which implies a use case but does not provide explicit guidance on when this tool is preferred over siblings like 'get_conversation' (for a single conversation) or 'get_transcript' (for a detailed transcript). There is no mention of when not to use it or alternatives.

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