analyze_article

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

With no annotations provided, the description carries the full burden. It states the tool returns JSON metadata, implying a read-only operation, but does not explicitly confirm this or disclose any side effects, rate limits, or authentication needs. The description adds some transparency about the output nature but lacks full disclosure.

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 two sentences with no wasted words. It front-loads the main action (structural analysis and metadata return) and adds context (use as source for AI generation). It is appropriately sized for the tool's simplicity, though it could be slightly more precise about output details.

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 2 parameters, no nested objects, no output schema, and 100% schema coverage, the description is adequate but not complete. It mentions the output format (JSON) and lists example metadata fields, but does not specify the exact structure or any edge cases. Relative to the complexity, it meets a minimum viable standard.

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 100% because both law_name and article_number have descriptive examples in the schema. The description does not add new meaning beyond the schema, so the baseline score of 3 applies. No param-specific guidance is provided beyond what the schema already contains.

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 analyzes legal article structure and returns metadata like paragraph counts and reference statistics. It uses a specific verb-resource combination ('逐条の構造を解析し...メタデータを返す') and mentions the use case for AI summaries. However, it does not explicitly differentiate from sibling tools like get_law or search_law, which limits clarity for agent selection.

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 for structural analysis but provides no explicit guidance on when to use this tool versus alternatives (e.g., get_law for full text, search_law for searching). No when-not-to-use or prerequisite conditions are mentioned, leaving the agent to infer the tool's niche without concrete direction.

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