get_issues

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

No annotations are provided, so the description carries the burden. The verb '取' implies a read operation, and the description lists what is returned, but it does not explicitly state side-effect-free behavior, authentication requirements, or error handling. The read intent is reasonably clear.

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?

One compact sentence that front-loads the action and resource, then lists output contents. No filler or redundant information.

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 a single required parameter, an existing output schema, and a simple read operation, the description sufficiently covers the core purpose. It could mention edge cases (e.g., no issues found) but that is minor.

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 0%, but the description associates qid with a specific essay question ('某申論題'), adding context beyond the raw parameter name. However, it does not specify the format, source, or any constraints for qid.

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 states a specific verb ('取' – retrieve) and resource ('某申論題拆出的所有爭點' – all issues extracted from an essay question), and enumerates the return contents (issue name, doctrinal opposition, practical opinions). This clearly distinguishes it from sibling tools like get_issue_primer or get_issue_chain, which have different scopes.

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?

Usage is only implied: to fetch issues for a particular qid. No explicit guidance is given on when to choose this tool over siblings or when not to use it, but the context of retrieving all issues for a specific question is reasonably inferable.

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