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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false. The description adds behavioral context: it returns 'full text' and 'verifiable EUR-Lex citation URL', and explains input format flexibility. No contradictions.

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 concise sentences front-load the purpose, then provide usage examples and selector formats. Every sentence adds value with no redundancy.

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?

Despite no output schema, the description adequately covers return items (full text and citation URL) and input parameters. Given low tool complexity and full schema coverage, it provides sufficient context for an agent to use 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?

Schema coverage is 100%, so the description doesn't need to explain all parameters, but it adds value by detailing how the 'article' parameter accepts single numbers, comma-separated lists, and ranges with suffix support, which goes beyond the schema's brief description.

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 it returns full text with citation URLs, uses specific verb 'get' and resource 'article', and distinguishes from siblings like list_articles or get_document by highlighting it as 'THE article-level grounding tool' for quoting specific articles.

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 explicit guidance on article selector formats (single number, comma list, range) and gives examples (GDPR Art. 17, AI Act Art. 6). It implies primary use for article-level grounding but lacks explicit when-not-to-use or alternative tool recommendations.

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