jdra_get_weekly_report

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

With no annotations at all, the description carries the full behavioral burden. It does disclose the most important non-obvious trait — '(없으면 lazy-create)' — warning that this is not purely a read operation and may create the report/field sets if absent. However, it does not describe the response shape or the implications of the lazy-create side effect, which matters because downstream mutation tools depend on this state.

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?

A single compact Korean sentence that front-loads the action (조회), then adds the lazy-create caveat, then the usage context. Every word carries information; there is no filler or redundancy.

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 zero-parameter getter with no output schema, the description is largely sufficient: it names what is retrieved, discloses the side-effect behavior, and explains why an agent would call it. The only gap is the lack of any hint about the response structure (field set IDs/names), which would help an agent act on the result, but this is a minor omission for a simple lookup tool.

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 tool has zero parameters, so the baseline is 4 and there is no parameter gap to compensate for. The description appropriately focuses on what the call returns (the weekly report and field set list) rather than inventing parameter guidance.

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 (조회한다/retrieves), a specific resource (내 주간보고와 필드셋 목록/my weekly report and field sets), and a distinct purpose (deciding which field set to use for issues). This functionally separates it from the sibling mutation tools like jdra_add_issue_to_weekly_report, but it does so implicitly rather than naming a sibling, so it stops short of a 5.

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 closing clause '어느 필드셋에 이슈를 넣을지 정할 때 참고' (refer to this when deciding which field set to put issues in) gives a clear when-to-use scenario tied to the weekly-report workflow. It does not explicitly state exclusions or name alternative tools, but the usage context is unambiguous.

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