search_agent_directory

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

With no annotations, the description carries the full burden. It discloses the live ERC-8004 registry source, the scale (110,000+ agents, 50+ chains), and the return fields (identity, owner, reputation, protocols, verification status, links). This is strong context for a search tool, though it could add explicit read-only confirmation or rate-limit info. 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?

The description is well-structured: a clear opening purpose, a data-source/return-value paragraph, and impactful examples. Every sentence earns its place—there is no fluff. Length is appropriate for the tool's complexity.

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?

Despite no output schema, the description explains return values comprehensively. It also provides context about data source, chain coverage, and example use cases. With 5 optional parameters and no annotations, this is a nearly complete picture for an agent to decide when and how to invoke the tool.

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%, and the description adds a valuable mapping layer via examples: 'trading agents on Base' maps to query+chain, 'MCP agents' maps to capabilities, 'high reputation agents' maps to minReputation. This goes beyond the schema's individual field descriptions and shows how parameters combine to fulfill natural language intents.

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 a specific action ('Search the AI agent directory') with the resource and scope ('registered agents by name, capability, protocol support, or reputation'). It distinguishes itself from siblings like search_ens_names (ENS names) and get_agent_reputation (single agent reputation) by focusing on directory-wide search with multiple filters.

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 examples give concrete usage scenarios ('trading agents on Base', 'MCP agents', 'high reputation agents') that implicitly teach when to use this tool. However, it does not explicitly mention alternatives or when not to use it, such as saying 'for a single agent's reputation, use get_agent_reputation instead.' Still, the context is clear and actionable.

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