generate_issue

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

There are no annotations, so the description is the only source of behavioral transparency. It fails to disclose whether the tool writes to GitHub, returns a data structure, or requires authentication, and it doesn't describe any side effects.

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, grammatically clean sentence with no filler words. However, it could have been slightly more informative while still being concise, so 4.

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?

Despite the rich parameter schema, the description leaves major context gaps: no output schema, no side effects, and no distinction from create_github_issue. The tool's actual function in the workflow remains ambiguous.

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 covers 100% of parameters with descriptions, so the baseline is 3. The description's mention of 'issue description, issue details, and repository labels' loosely maps to the schema but adds no new semantics beyond what the schema already provides.

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 uses a specific verb 'generate' and resource 'structured GitHub issue', but it doesn't differentiate from the sibling create_github_issue. 'Generate' is ambiguous about whether the tool actually creates the issue on GitHub or simply produces a structured data object.

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?

No guidance is given about when to use generate_issue versus create_github_issue, check_duplicate_issue, or list_github_labels. There is no mention of prerequisites, workflow order, or exclusions.

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