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

Annotations already declare the operation as read-only and non-destructive, so the safety profile is covered. The description adds meaningful context beyond that by stating results are 'stable, context-first' and 'descriptive concepts, not universal symbolic definitions,' which helps set agent expectations about output semantics. This exceeds the minimum bar for transparency.

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 long, with the first sentence delivering the core purpose and the second clarifying the nature of results. Every word adds value, and it avoids redundancy with the title or schema.

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 existence of an output schema and comprehensive annotations, the description covers the essential context for a simple search tool. It does not elaborate on pagination or error behavior, but these are not critical for a straightforward lookup. The description satisfies the bulk of contextual needs.

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 has 100% description coverage for both parameters, including examples and constraints. The description does not add significant parameter-level detail beyond what the schema already provides, so the baseline score of 3 is appropriate.

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 searches DreamGraph's vocabulary for a dream element or experience, using a specific verb and resource. It distinguishes itself by noting results are descriptive concepts rather than universal symbolic definitions, which hints at its unique scope. However, it does not explicitly contrast with the sibling tool parse_dream as the high-calibration example does.

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 looking up dream-related concepts, providing a clear context for when to use it. It does not mention alternatives or exclusions, such as when parse_dream would be more appropriate. Thus, it is clear but lacks explicit when/not-to-use guidance relative to siblings.

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