get_issue

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

With no annotations, the description carries full responsibility for behavioral disclosure. It names returned fields but omits details like permissions needed, error handling for invalid IDs, or whether archived issues are included. The transparency is basic and functional.

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, well-front-loaded sentence with clear purpose and a concise list of included details. It avoids fluff but could be slightly more structured (e.g., bullet points) for easier scanning.

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 simplicity (one required parameter, exists output schema), the description covers core functionality but misses usage context (e.g., scope of issues accessible, pagination for comments) that would aid an agent in selecting this tool over similar ones.

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 schema coverage is 0% with no parameter description. The description does not add any detail about the 'issue_id' parameter (e.g., format, type hints), relying entirely on the parameter name which, while intuitive, insufficiently compensates for the lack of schema documentation.

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 retrieves full issue details and enumerates specific included fields (comments, labels, assignee, dates), distinguishing it from sibling tools like list_project_issues or search_issues which return summaries or filtered lists.

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 implicitly suggests using the tool when you need a comprehensive view of a single issue, but it provides no explicit guidance on when to avoid it (e.g., for bulk operations) or links to alternatives like search_issues for filtered queries.

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