ask_question

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

With no annotations, the description must carry behavioral transparency. It discloses that responses are AI-powered and context-grounded, which is useful. However, it does not mention limitations such as potential inaccuracy, access restrictions, or how the context is obtained.

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, clear sentence that states the action, target, and result without any wasteful words. It is optimally concise and front-loaded.

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 tool is moderately complex (AI Q&A over repositories), and the description/schema together convey the essential information for invocation. However, it lacks behavioral nuance (e.g., how answers are generated, limitations) and does not reference the output schema, though that is optional when an output schema exists.

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 descriptions cover both parameters with 100% coverage, so the description does not need to add parameter-level details. It adds minimal value by reinforcing the 'question' and 'repository' concepts, but nothing beyond the schema.

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 identifies a specific action ('Ask any question') on a specific resource ('a GitHub repository') and the expected outcome ('AI-powered, context-grounded response'). It is distinct from sibling tools (read_wiki_contents, read_wiki_structure), though it does not explicitly reference them.

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 usage when you need to ask a question about a repository, but it does not provide explicit guidance on when to prefer this tool over alternatives, nor does it mention any exclusions or prerequisites.

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