List Issues

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

Annotations already indicate the tool is read-only and non-destructive. The description adds valuable behavioral context: pagination limits with warnings (e.g., >10 pages or 300 items), and the possibility of returning an error if the issue tracker is disabled. This goes 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 is well-structured with separate sections for Args, Returns, and Note. It is concise and each sentence adds value. There is no redundant or filler content.

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 complexity of the tool (11 parameters, pagination, error cases) and the presence of an output schema (so the description doesn't need to detail return structure), the description covers all necessary aspects: parameters, usage notes, and edge cases.

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 0% description coverage, meaning the schema only provides names and types. The description compensates fully by explaining each parameter, including valid values (e.g., state: new, open), default values, and a detailed example for the 'q' parameter with BBQL syntax.

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 it lists issues in a repository's issue tracker with filtering and pagination. The verb 'List' and resource 'issues' are specific, and among the many sibling tools focused on pull requests and issue comments, this tool's purpose is distinct.

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 overview of the tool's functionality and its parameters, but it lacks explicit guidance on when to use this tool versus alternatives like 'get_issue' for a single issue. The usage is implied but not contrasted.

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