get_conversation_users

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

Annotations indicate readOnlyHint=true and destructiveHint=false, so the agent knows this is a safe read operation. The description doesn't add behavioral context beyond this (e.g., rate limits, authentication needs, or what 'Get' entails like pagination or format), but it doesn't contradict the annotations. With annotations covering safety, the description adds minimal value.

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. It's front-loaded and directly states the tool's purpose, making it easy to parse quickly. Every word earns its place, adhering to best practices for conciseness.

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 annotations for safety but no output schema and low parameter coverage, the description is incomplete. It doesn't explain the return values (e.g., list of users, their roles) or provide enough context for effective use, especially with sibling tools that might overlap. For a read operation with one parameter, more detail would improve completeness.

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 one parameter 'id' with 0% description coverage, and the tool description doesn't explain what 'id' refers to (e.g., conversation ID, user ID). Since schema coverage is low, the description should compensate but doesn't, leaving the parameter undocumented. However, with only one parameter, the baseline is slightly higher, but the lack of detail limits the score.

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 'Get users in a conversation' clearly states the verb ('Get') and resource ('users in a conversation'), but it's vague about scope (e.g., all users, active users, or participants) and doesn't distinguish it from sibling tools like 'get_conversation' or 'search_users', which might overlap in functionality. It's adequate but lacks specificity.

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 no guidance on when to use this tool versus alternatives such as 'get_conversation' (which might include user data) or 'search_users' (for broader user queries). There's no mention of prerequisites, context, or exclusions, leaving the agent to infer usage based on the name alone.

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