find_law_article

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions being 'ULTRA SMART & FAST' and handling complex patterns automatically, which adds useful context about performance and functionality. However, it lacks details on error handling, rate limits, or authentication needs, leaving gaps for a tool with no annotation coverage.

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 and front-loaded with the core purpose, followed by key features and parameter details. Every sentence adds value, such as specifying law support and pattern handling, with no redundant information, making it efficient and easy to parse.

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 tool's complexity (handling Japanese legal articles with automatic pattern parsing) and no annotations or output schema, the description is adequate but incomplete. It covers the purpose and parameters well but lacks details on return values (only mentions a dict with content and metadata without specifics), error cases, or performance limitations, which could hinder agent usage.

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?

The description provides clear examples for both parameters (law_name and article_number), such as '民法' for law_name and '192' or '325条の3' for article_number, which adds meaningful context beyond the schema's 0% coverage. This compensates well for the lack of schema descriptions, though it doesn't fully explain all possible formats or constraints.

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 as finding a specific article in Japanese law, specifying it's 'ULTRA SMART & FAST' with support for 16+ major laws and automatic handling of complex patterns like 条の2, 項, 号. This distinguishes it from sibling tools like 'search_laws' or 'get_law_content' by focusing on precise article retrieval rather than broader searches or content fetching.

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 by mentioning support for 16+ major laws and automatic pattern handling, which suggests it's for precise article lookup. However, it doesn't explicitly state when to use this tool versus alternatives like 'batch_find_articles' for multiple articles or 'search_laws' for broader queries, leaving some ambiguity in sibling tool differentiation.

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