list_issues

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

With no annotations, the description carries the burden. It discloses parameter behaviors (defaults, allowed values) but lacks details on pagination, return format, or edge cases like empty results. It adequately explains input but not output behavior.

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 concise: a one-line purpose followed by a structured Args block with one line per parameter. No extraneous text, every sentence serves a purpose. Front-loaded with purpose.

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?

Input parameters are well explained, but the description lacks details about the output (e.g., what fields are returned, structure of issue objects). Given no output schema, this gap reduces completeness. Error handling or ordering behavior beyond sort is also missing.

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 0%, so the description fully compensates by explaining all 7 parameters with context such as defaults, allowed values (e.g., status: 'open','closed','*'), and format (e.g., sort: 'updated_on:desc'). This adds significant value beyond the bare 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 states the tool's purpose as '일감 목록 조회' (List issues), which is a specific verb+resource combination. It distinguishes itself from siblings like get_issue (single issue) and create_issue by focusing on listing multiple issues.

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 explains parameters for filtering but does not explicitly state when to use this tool versus alternatives like get_issue or list_projects. No usage guidance or exclusions are provided.

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