watch_action_plan

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

With no annotations provided, the description carries the full behavioral disclosure burden. It explains that the tool returns an action plan and a list of next MCP calls rather than performing legal analysis. This is meaningful transparency about output type, though it does not specify whether the tool itself executes those calls or if any side effects occur.

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 compact and front-loaded: the first sentence states the core function, and the second adds a valuable clarification about non-legal output. No unnecessary repetition or filler is present.

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 simple generative tool, the description covers purpose and output type, and the output schema presumably handles return-value documentation. However, parameter semantics for 'age' and 'limit' are missing, and there is no explicit guidance on selecting this tool over siblings. The description is adequate but not fully complete.

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 must compensate for the missing parameter documentation. It mentions '특정 입법 주제' which maps to the 'topic' parameter, but it provides no guidance about 'age' or 'limit'. Since two of three parameters are completely unexplained, the description only partially compensates.

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 a specific action ('generates an action plan and list of next MCP calls') and a specific subject ('track changes on a specific legislative topic'). It also disambiguates itself from legal advice by clarifying it returns a monitoring procedure. This makes the tool's purpose very clear.

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 primary usage context is explicitly stated: use this for tracking changes on a specific legislative topic. The description does not name alternative sibling tools or explicitly say when not to use it, but the purpose-driven framing gives solid guidance. The note about not being legal advice also helps set expectations.

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