check_precedent_odds

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds valuable context about the tool's behavior: it searches precedents, analyzes outcomes (인용/기각/파기), and extracts key factors. The Returns section also clarifies what the agent can expect. No contradictions with annotations.

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 well-structured with sections for purpose, arguments, returns, and examples. It is front-loaded with a concise overview and each sentence in the Args section adds necessary detail. No redundant content, and the format is easy to scan.

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 description covers the tool's purpose, parameter details, return summary, and examples. It lacks deeper details like error handling, jurisdiction, or analysis methodology, but given the tool's moderate complexity and strong annotations, this is sufficient for an agent to select and invoke it correctly.

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%, and the description effectively compensates by explaining each parameter in the Args section: query, display, top_n, oc, and type. It provides meanings, defaults, and examples (e.g., display max 100, default 20; type options JSON/XML/HTML). This far exceeds what the schema offers.

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 function: 'Find precedent statistics and key outcome factors for a legal question' and distinguishes it from sibling search tools by emphasizing outcome analysis and 'legal odds'. The verb 'Find' is specific, and the scope is well-defined, setting it apart from general precedent search tools.

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 provides clear context: 'Useful for assessing legal odds' indicates when to use it. However, it does not explicitly mention alternatives or when not to use it, missing a bit of exclusions. This is still sufficient for an agent to identify the appropriate use case.

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