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

Annotations already convey non-read-only, non-idempotent, and open-world nature. The description adds useful context: it uses the project's configured repo/assignee unless overridden and embeds the AI prompt in the body, which goes beyond the annotations without contradiction.

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 two concise, front-loaded sentences with zero waste. Every phrase contributes, from the core action to the defaultValue context and prompt embedding.

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?

With output schema, annotations, and a 100% schema coverage, the description sufficiently covers purpose, defaults, and body content. The tool is simple and the description leaves no major gaps.

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 covers all 3 parameters, so baseline is 3. The description adds meaning by explaining that repo and assignees default to project configuration unless overridden, which is not evident from the schema alone.

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 from an annotation' with a specific verb and resource. It distinguishes from sibling read-only tools like list_annotation_issues and generate_prompt by specifying the creation action and source.

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 implies when to use the tool by stating it creates an issue from an annotation and uses configured defaults. It gives context about repo and assignee override behavior but does not explicitly name alternatives or exclusions.

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