Enrich restaurant

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

Annotations already indicate readOnly, idempotent, and open world. The description adds value by disclosing that the tool does not return certification/free-from facts, and explains the matching confidence threshold behavior. This provides useful behavioral context beyond what annotations offer.

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 three sentences, each adding essential information: purpose and returned data, exclusions, and low-confidence behavior. It is front-loaded and concise without 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?

Given the output schema exists, the description covers all necessary context: purpose, input options, constraints, and edge-case behavior. It is complete for a read-only enrichment tool with no need for additional state or authentication details.

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%, so parameters are well-documented. The description adds semantic value by explaining that google_place_id provides the highest match confidence, and that compass_id is for direct lookup. This enhances the agent's understanding of parameter use.

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 specific verb 'Match' and resource 'restaurant enrichment data' clearly defines the tool's function. It lists returned data types (VeganScore, vegan dietary profile, evidence) and explicitly states what is not returned (certification/free-from facts), providing a precise purpose that distinguishes it from siblings.

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 explains the input parameters (name and address as primary matching; compass_id or google_place_id as alternatives) and describes the behavior when confidence is low (returns 'matched: false' with candidates). While it doesn't explicitly state when not to use this tool, the context for enrichment vs. search/decide is implied by the sibling tool names.

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