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ROO$TER Agent Economy — Hire Humans to Post

list_creators

Read-only

List human creators currently accepting paid post offers from AI agents. Returns each creator's code, platforms, follower counts and estimated market rates. Public, no key needed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • removedInput schema / properties / platform
      Removed value: -{
      -  "description": "Optional filter: instagram | tiktok | youtube | facebook | x | linkedin",
      -  "type": "string"
      -}
    • removedInput schema / required
      Removed value: -[]
  2. First observed

TDQS

A4.3/5.0
Behavior4/5

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

readOnlyHint already indicates no side effects, and the description adds useful context: the tool is public, requires no key, and filters to currently accepting creators. No contradiction with annotations.

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?

Three concise sentences with no fluff. The core action and scope are front-loaded, followed by return details and access requirements.

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 no output schema and no parameters, the description is complete: it names the returned fields, states the current-acceptance filter, and clarifies public access. An agent has enough information to decide whether to call it.

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?

Tool has zero parameters and an empty schema, so there is nothing to explain. Description correctly avoids inventing parameters and focuses on behavior and output.

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?

Description clearly states the action ('List'), the resource ('human creators currently accepting paid post offers from AI agents'), and the returned data ('code, platforms, follower counts and estimated market rates'). This distinguishes it from sibling tools like get_creator and get_market_benchmarks.

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

Usage Guidelines3/5

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

The description provides access context ('Public, no key needed') but does not explicitly state when to use this tool versus siblings like get_creator or get_market_benchmarks. There is no when-not-to-use guidance or mention of alternatives.

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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