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

With no annotations, the description carries the full burden. It discloses that no API key is required, that it returns authentic text with metadata and attribution, and that output is truncated to max_chars. However, it does not mention error handling, rate limits, or what happens if the ID is invalid, which is a notable gap for a fetch tool.

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?

Two sentences, no filler. The primary purpose is front-loaded, and the typical flow is stated succinctly at the end. Every sentence contributes to understanding.

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?

For a simple fetch tool with 3 parameters and no output schema, the description covers the purpose, the usage flow, the authentication requirement, and the output nature. It does not detail error cases, but it is sufficient for an agent to call the tool 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?

Although schema coverage is 100%, the description adds meaningful context by clarifying that law_id can be a revision_id from search results and by explaining the truncation behavior. It also frames the article parameter as optional extraction, adding value 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 opens with a specific verb ('Fetch') and resource ('original Japanese text of a law'), and explicitly distinguishes itself from the search siblings by referencing 'search_japanese_law' as the source of the IDs. The typical flow clarifies its role in the pipeline.

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?

It clearly states the dependency on search_japanese_law and gives a typical flow (search_japanese_law -> get_law_text), which guides when to use it. It does not explicitly list alternatives or exclusions, but the sibling tools are search-focused and the context makes the usage obvious.

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