List Issues

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

Beyond the readOnlyHint annotation, the description discloses the exact response structure ({ items, pagination } with count, current_page, has_next), the default page_size (30), and hints at the cost of pagination by suggesting filters. It also notes the pagination data is 'read from Taiga,' grounding the behavior. No contradictions with annotations.

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 three sentences, each earning its keep: purpose, response schema/defaults, and a cost-saving tip. It is front-loaded with the core action and avoids redundancy, making it efficient and scannable.

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?

For a list tool with 10 parameters and no output schema, the description provides the response envelope, default page size, and strategic usage advice. It does not walk through every parameter, but the schema already covers key ones (page, page_size, verbosity, project). The description is sufficiently complete for typical use, though it could clarify how filters combine or mention q.

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 description coverage is only 40%, so the description has a burden to explain parameters. It mentions that the tool is 'optionally filtered' and that type/status/priority/severity/tags/assigned_to ids can be discovered via issue_filters_data, adding meaning for those previously undocumented params. However, it does not explain the `q` parameter or specific semantics of each filter beyond their names, leaving some gaps.

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 opens with 'List issues, optionally filtered by the given query parameters,' which clearly states the verb (list) and resource (issues) and differentiates from sibling tool issue_get by implying list semantics. It also distinguishes from issue_filters_data by recommending that tool for discovering valid ids, making the purpose distinct.

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 explicitly directs users to use issue_filters_data to discover valid filter ids 'cheaply' instead of paging through results, providing an when-to-use alternative. It also implies the tool is for listing with optional filters, but does not explicitly state when not to use it (e.g., for a single issue) or contrast with other list siblings like task_list, though names make this obvious.

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