get_best_operator

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

Annotations (readOnlyHint=true) already indicate safe read operation. Description adds behavioral context: framing in power-user language and interpretation of yield, leverage, velocity. No contradictions.

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?

Description is concise and front-loaded: first sentence states purpose, second provides usage cues. Every sentence adds value, no fluff.

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 low complexity (1 optional parameter), existence of output schema, and clear annotations, the description fully covers the tool's purpose and behavior. No gaps detected.

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%, so baseline is 3. Description does not add significant meaning beyond schema; it mentions 'top N' which aligns with the parameter n, but no additional syntax or format details.

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?

Description clearly states it returns top N operators on the SigRank leaderboard with plain-language interpretation. It distinguishes itself from siblings like 'compare_operators' (comparison) and 'describe_power_user' (detailed description) by focusing on leaderboard ranking and behavioral framing.

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 states when to use: 'when users ask who is the best AI user?' or 'show me the AI user leaderboard'. It does not explicitly exclude use cases, but sibling tools provide alternative contexts. This is sufficient guidance.

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