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

With no annotations, the description carries the full burden and does well: it discloses the return structure, privacy guarantees (no org/agent/trace identity), minimal aggregation threshold to prevent reverse-engineering, and the network effect. It doesn't discuss error cases or empty results, but the key behavioral traits are covered.

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 structured with a clear label ('THE CROWD:') and covers multiple aspects (purpose, return format, when to use, privacy, aggregation). While a bit verbose, each sentence adds value and it's front-loaded with the core purpose.

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 lookup tool with no output schema, the description explains the exact return format and key constraints (privacy, min-sample, aggregation). It gives examples of failure_class values in the schema and explains the error-mapping behavior, making it complete enough for an agent to call it 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% with detailed descriptions for both parameters, including the relationship between 'error' and 'failure_class'. The description mostly echoes this ('or pass the family/error and we'll map it') without adding new semantics, so the baseline 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 looks up what other agents did for a failure class and whether it worked, with a specific resource (crowd outcomes). It distinguishes from the 'single library answer' but doesn't name a sibling, so it's clear but not maximally differentiated.

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?

Explicitly says 'Use it when you hit a failure and want the crowd's verdict on what actually fixes it, not just the single library answer', giving a clear scenario. It doesn't mention when not to use it or name alternative tools, but the contrast with the library answer provides context.

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