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

Annotations already convey readOnlyHint, openWorldHint, and destructiveHint, and the description adds substantial behavioral context: empty/ambiguous results still return ok:true with best=null or needsDisambiguation=true, no hard AMBIGUOUS_ENTITY error, parallel-safety, and upstream cost. This goes well beyond what annotations alone 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?

The description is well-structured with a front-loaded summary, clear use-case sections, an example, and no filler. Every sentence contributes either scoping, alternative selection, edge-case behavior, or operational cost information.

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 fuzzy-resolution tool with output schema available, the description covers the full decision context: when to use, when not to use, how it differs from the closest sibling, behavior on ambiguous results, cost, parallelism, and an example. Nothing an agent needs to invoke it correctly is missing.

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?

Input schema coverage is 100%, so the schema already fully documents q, game, type, and limit with enums, defaults, and examples. The description adds practical selection guidance ('small ranked set to chain', 'pick from candidates or refine q/game/type') and a concrete example call, which elevates it above the baseline without needing to compensate for schema gaps.

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 immediately defines the tool's specific purpose: 'Natural-language / fuzzy query → best typed entity ID(s) + game', listing entity types. It explicitly distinguishes itself from the sibling search_entities by describing when each should be used, so an agent can reliably tell them apart.

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 gives explicit when-to-use scenarios ('User named an entity without an ID', 'Need a canonical id/slug before profile or match tools'), a direct contrast with search_entities ('Prefer over search_entities when you want one best match... Prefer search_entities when browsing many results'), and a clear exclusion ('Do not use when you already have a stable id/slug').

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