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t2000_agents

Look up registered on-chain AI agents in the t2000 directory. List agents by category or retrieve a full identity profile with a Sui address.

Instructions

Look up agents in the t2000 AGENT DIRECTORY (t2000.ai) — registered on-chain Agent IDs. Distinct from t2000_services (what agents SELL): these are the AGENTS themselves, with on-chain identity.

No address → the registered-agent list (filter with category/limit). With an address → the full identity profile (name, owner, links, on-chain record).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax listings to return (default 30)
addressNoAn agent's Sui address for the full listing (omit to list)
categoryNoFilter the list: ai-models | data-feeds | finance | research | dev-tools | creative | other
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly explains the two modes (list vs. detail) and what information is returned (name, owner, links, on-chain record). It does not explicitly state that the operation is read-only, but 'look up' strongly implies it, and no side-effect behavior is hidden.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and well-structured: a single opening sentence states the core purpose, followed by a sibling distinction, and then a clear conditional breakdown for the two usage modes. Every sentence adds meaningful information without redundancy or fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (two modes, three optional parameters, no output schema), the description covers all essential aspects: what the tool returns in each mode, the presence of filtering options, and the on-chain identity nature. The content is sufficient for an agent to correctly select and invoke the tool without requiring additional context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% for all three parameters, so a baseline of 3 applies. The description adds value beyond the schema by explaining the behavioral distinction of including an address (full identity profile) versus omitting it (list), and clarifies that category and limit are filtering/pagination mechanisms. This extra context raises the score above baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: looking up agents in the t2000 AGENT DIRECTORY, specifically on-chain registered Agent IDs. It uses a specific verb and resource, and explicitly distinguishes itself from t2000_services, which sells agent services, making the purpose highly clear.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit usage guidance: with no address, it lists registered agents filtered by category/limit; with an address, it returns the full identity profile. It also names a sibling tool (t2000_services) to indicate what this tool is NOT for, offering clear when-to-use vs. alternative context.

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

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