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

Annotations already mark the tool as read-only and idempotent, and the description adds substantial non-obvious behavior: definitions are resolved to the cited act even if repealed, undefined terms are refused with suggestions rather than substituted, and references_in exposes reverse edges. These disclosures go well beyond what the structured hints provide.

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?

Every sentence earns its place: the question front-loads purpose, and the remaining sentences each add a distinct fact about resolution, refusal, or reverse-edge behavior. Although dense, there is no filler or repetition of schema content.

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?

With a rich output schema and 100% parameter coverage, the description does not need to restate return structures. It covers critical edge cases such as repealed citations, undefined terms, and corpus-wide scope, making it largely complete. It lacks explicit routing guidance relative to sibling tools, but that gap is already reflected in usage_guidelines.

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 input schema already documents all five parameters with 100% coverage, so the baseline is 3. The description adds interpretive value by explaining resolution policy, the no-substitution rule for unknown terms, and the meaning of reverse-edge references, which helps an agent understand both the term and comparison parameters more deeply.

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 concrete interrogative that captures the tool's core function: what a term means, where, and since when. It then enumerates distinctive outputs — verbatim and resolved definitions, clustering, chronological/concurrent views, and word-level comparisons — which clearly separate it from siblings such as compare_versions and search_defined_terms.

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 clear constraints and behavioral context, such as resolution following the CITED version and refusal for undefined terms, but it never explicitly states when to choose this tool over alternatives like compare_versions, get_provision, or search_defined_terms. The usage context is implied rather than spelled out.

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