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

No annotations are provided, so the description carries the full burden. It does disclose a meaningful behavioral trait — only anonymous aggregates are returned and no personally identifying information is included — which is genuinely useful and non-obvious. It does not cover permission/auth requirements, error behavior, or whether reports are available only for ended meetings, so for an unannotated read tool this is adequate but incomplete.

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?

Three short sentences, each carrying distinct payload: what is returned, the privacy constraint, and the usage trigger. Front-loaded with the purpose. Dense and waste-free, though the parenthetical content enumeration makes the first sentence slightly heavy.

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?

With no output schema, the description usefully enumerates the report's return sections (agenda, vote tally, decision/owner/deadline, AI summary) and the anonymity guarantee, which covers the main gaps. A simple one-parameter read tool with no annotations is described well enough to call correctly, though permission prerequisites remain unstated.

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 100% for the single room_code parameter (with min/max length and an example), so the schema already does the work. The description adds no format or semantics beyond that, which is the correct baseline when the schema is self-sufficient.

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?

States a specific verb (가져온다/fetch) plus the exact resource and its contents: agenda report (agenda → vote tally → decision/owner/deadline) and AI minutes summary. An agent knows precisely what comes back, though it does not distinguish itself from lookalike siblings such as get_carryover or get_board_results.

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?

Gives a concrete trigger condition — use when propagating the decisions of a finished meeting into follow-up work (끝난 회의의 결정사항을 후속 업무로 전파할 때). No explicit exclusions or named alternatives, so the agent must still infer why not get_carryover, which is a plausible substitute for the same follow-up scenario.

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