create_issue

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

No annotations are provided, so the description carries the full burden. It only mentions rejection of non-existent labels but does not disclose other behavioral traits such as authentication requirements, creation scope (e.g., which repository), idempotency, or side effects. A mutation tool needs more 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?

Two concise sentences with no waste. The key information is front-loaded: the purpose and a critical usage guideline. Every sentence earns its place.

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?

The description covers creation and label validation but omits the return value (e.g., issue number or URL) and potential side effects. For a tool with no output schema, describing the return value would improve completeness. It is minimally adequate given the tool's simplicity.

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?

Schema coverage is 100%, with all three parameters described. The description adds value beyond the schema by specifying that label names must come from list_labels, which clarifies validity constraints. However, it does not add significant meaning for title or body beyond what the schema states.

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 'Create a GitHub issue,' specifying the verb and resource. It explicitly mentions using list_labels for label validation and distinguishes from siblings (e.g., create_pr, list_labels) by focusing on issue creation.

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 explicit guidance: 'Use list_labels first to pick valid label names — non-existent labels are rejected.' This tells the agent when to use a sibling tool as a prerequisite and clarifies that invalid labels cause rejection.

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