linear_get_user_issues

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 mentions that it 'gets issues' and includes parameters for archived issues and limits, but it doesn't describe key behaviors like whether this is a read-only operation, what permissions are needed, how results are returned (e.g., pagination, format), or any rate limits. For a tool with no annotations, this is a significant gap in transparency.

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 appropriately sized and front-loaded: it starts with a clear purpose statement, followed by a bullet-point-like list of parameters with brief explanations. Every sentence earns its place by adding value, and there's no wasted text, making it highly efficient and well-structured.

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 moderate complexity (3 parameters, no annotations, but with an output schema), the description is partially complete. It covers the purpose and parameters well, but since there's no output schema mentioned in the context signals (though 'Has output schema: true' is noted, the description doesn't reference it), it lacks details on return values or error handling. This leaves some gaps for an AI agent to fully understand the tool's behavior.

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 description adds meaningful semantics beyond the input schema: it explains that 'user_id' can be omitted for the authenticated user, clarifies that 'include_archived' includes archived issues, and notes the default for 'limit' is 50. Since schema description coverage is 0%, the description effectively compensates by providing clear parameter meanings, though it doesn't cover all potential nuances (e.g., format of user_id).

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's purpose: 'Get issues assigned to a user.' It specifies the verb ('Get') and resource ('issues assigned to a user'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'linear_search_issues' (which might search issues more broadly), so it doesn't reach the highest score.

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 some implied usage context: it mentions that 'user_id' can be omitted for the authenticated user, suggesting when to use this parameter. However, it doesn't give explicit guidance on when to choose this tool over alternatives like 'linear_search_issues' or mention any prerequisites or exclusions, leaving gaps in usage direction.

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