get_issue

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

With no annotations provided, the description carries the full burden of behavioral disclosure but only states the basic action ('Get details'). It doesn't mention whether this is a read-only operation, what permissions are required, how errors are handled, or the format of returned details. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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, direct sentence with no wasted words. It front-loads the core action ('Get details') and specifies the target ('a specific issue'), making it efficiently structured for quick comprehension by an AI agent.

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 retrieving issue details in a version control system, the description is incomplete. With no annotations, no output schema, and minimal behavioral context, it fails to address key aspects like authentication needs, error cases, or the structure of returned data. This makes it inadequate for reliable tool invocation in a real-world context.

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 description coverage is 100%, with clear descriptions for all three parameters (workspace slug, repository slug, issue ID). The description adds no additional semantic context beyond what the schema provides, such as explaining how these identifiers relate or where to find them. This meets the baseline for high schema coverage but doesn't enhance parameter understanding.

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 ('Get') and resource ('details of a specific issue'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'list_issues' or 'get_pull_request' which also retrieve issue-related information, so it falls short of a perfect 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 no guidance on when to use this tool versus alternatives like 'list_issues' (for multiple issues) or 'get_pull_request' (for pull requests, which are a type of issue in some systems). It lacks explicit context about prerequisites or exclusions, leaving the agent to infer usage from the tool name alone.

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