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

No annotations are provided, so the description carries full burden for behavioral disclosure. It mentions the plan includes static and dynamic checks but does not state whether the tool is read-only or has side effects. For a plan-returning tool, it likely does not modify state, but this is not confirmed.

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: two sentences plus a key insight. All content is relevant and front-loaded with the core action. The quote adds useful context without excess.

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?

The tool produces a plan as output, but no output schema is provided and the description does not explain the return format or structure. For a tool that returns a complex artifact (plan), the agent needs more guidance on how to interpret the output. Input documentation is sufficient.

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?

Input schema coverage is 100% with descriptions for both parameters ('claims' and 'target'). The description adds context about the tool's purpose but does not enhance parameter semantics beyond what the schema already provides. Baseline 3 is appropriate.

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 that the tool returns a verification plan ('수신측 거미 검증 계획을 반환한다') and elaborates on its content (static dimension + E2E probes). It conveys a specific verb-resource pairing and the tool's purpose is distinct, though it does not explicitly differentiate from sibling 'baton_verify'.

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 implies usage context: when verification with actual observation ('완료 주장마다 실제 관측을 요구') is needed. However, it does not provide when-not-to-use guidance or mention alternative tools like 'baton_verify'. The context is present but not explicit.

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