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

No annotations provided, so the description must fully disclose behavioral traits. It does not mention read-only nature, pagination, ordering (e.g., descending by score), or any side effects. The description is minimal and fails to reveal basic behavioral context beyond the action itself.

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?

Two sentences, front-loaded with the core purpose. No wasted words. The first sentence states action and scope, the second gives usage guidance. Highly concise and well-structured.

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?

The tool is simple (2 optional params, no output schema). The description is adequate for basic usage but does not explain what constitutes a 'score', the return format, or any edge cases. For a leaderboard tool, slightly more detail on output would improve completeness.

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 descriptions for both parameters (limit and network). The description adds no additional meaning beyond 'top-scored'; it does not explain how limit affects results or what networks are valid. Baseline 3 is appropriate as schema already explains the parameters.

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 it lists top-scored onchain AI agents on Base, using a specific verb ('list') and resource ('top-scored agents'). It distinguishes from siblings like mainstreet_score (which likely shows score for a single agent) by focusing on a leaderboard, but does not explicitly differentiate from other discovery tools like mainstreet_bazaar_scored.

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?

Provides explicit usage scenarios: 'when the user asks 'who is best at X' or wants discovery without a specific intent.' This gives clear context for when to invoke, though it does not mention when not to use or suggest alternative tools among the many siblings.

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