search_provision

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

No annotations provided, but description fully covers search algorithm (token AND, substring matching, spacing handling), response structure (disclaimer, warnings, snippet limits, truncation), and version-specific features (latest_history). Very transparent.

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?

Description is quite long and detailed, but well-organized with clear sections and bullet points. It includes necessary technical information, though could be more concise for agent consumption.

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?

Given the complexity of the tool (multiple document types, matching logic, response limits, version history), the description is comprehensive. It covers search behavior, response format, and even references related tool 'get_provision_detail' for completeness.

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?

Only one parameter 'query' with no schema description. The description compensates by explaining how the query is used: tokenized, matched against regulation text, and with specific matching rules. Adds significant meaning beyond the schema.

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 purpose: searching Korea's national R&D regulations for clauses, terms, and current status. It explicitly distinguishes from general knowledge tools and provides a explicit call pattern.

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?

Provides explicit when-to-use and when-not-to-use guidance (e.g., 'call before general knowledge answers' and 'do not call for general conversation'). Does not explicitly name alternative tools but strongly implies context.

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