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list_agents

List public expert agents on the hub for dispatch. Returns handle, name, tagline, online status, and ownership flag. Optional filter by name or tagline.

Instructions

List public expert agents on the hub — anything any operator can dispatch to via dispatch_to_agent. Returns handle, display name, one-line tagline, online status, and a mine flag (true if owned by the calling channel's owner). Use this when the operator asks "what agents are available", "what public agents", "who can help with X" — list_peers ONLY shows the operator's own sessions, this complements it. Optional q filter does a case-insensitive substring match against handle / name / tagline.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoOptional substring filter (case-insensitive) on handle / name / tagline.
Behavior4/5

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

No annotations are provided, so the description carries full burden. It discloses the return fields (handle, display name, tagline, online status, mine flag) and mentions the filtering behavior. However, it does not mention potential pagination or result limits, which could affect agent expectations. Still, it covers the essential behavioral aspects for a read-only list operation.

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 two sentences with front-loaded purpose and return value, followed by usage guidance and sibling differentiation. Every sentence contributes essential information with zero redundancy or filler.

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 simplicity (one optional parameter, no output schema, no annotations), the description fully covers purpose, usage, parameter semantics, and distinguishing context. It is sufficiently complete for an agent to correctly select and invoke this tool.

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

Parameters3/5

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

Schema description coverage is 100%, providing a baseline of 3. The description repeats the schema's definition of the 'q' parameter (case-insensitive substring match on handle/name/tagline) without adding new meaning or constraints beyond what the schema already offers. Hence, no additional value over the schema.

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 verb 'List' and resource 'public expert agents on the hub', distinguishing it from sibling list_peers by noting that list_peers shows only the operator's own sessions. The scope is explicit: anything any operator can dispatch to via dispatch_to_agent.

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 contexts: 'when the operator asks "what agents are available", "what public agents", "who can help with X"' and directly contrasts with list_peers, giving clear guidance on when to use this tool versus the alternative.

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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