get_economic_mandate
Read the authenticated canonical economic mandate.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Read the authenticated canonical economic mandate.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, and the description's 'Read' wording is consistent with that. The words 'authenticated canonical' add minor context about the source and authorization, but no additional behavioral traits such as return format or required authentication context are disclosed.
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 a single clear sentence with no filler or repetition. It is appropriately sized for a zero-parameter read operation.
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?
For a simple no-input read tool, the description is minimally sufficient: an agent can invoke it without arguments. However, the domain-specific term 'economic mandate' is never explained, and no output schema exists to clarify what the returned mandate looks like, so an agent may not fully understand what result to expect.
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?
The tool has zero parameters, so the description does not need to explain parameter meanings. The baseline of 4 is appropriate because there is no parameter-related ambiguity to resolve.
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 uses a specific verb ('Read') and names a specific resource ('authenticated canonical economic mandate'), so it clearly states what the tool does. However, it does not explicitly differentiate from the similar sibling tool check_economic_mandate, leaving some ambiguity about how 'read' differs from 'check'.
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?
There is no guidance about when to use this tool versus alternatives. The sibling list includes check_economic_mandate, which likely serves a related purpose, but the description does not explain which one an agent should choose in a given situation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
There are multiple clusters of near-duplicate tools: earn, earn_now, earn_loop, find_money_opportunities, search_global_earn, and several rank_real_profit_opportunities variants. Even with descriptions, an agent would struggle to choose reliably among dozens of overlapping search, earn, and ranking entry points.
Most tools follow a snake_case verb_noun pattern, which provides some consistency. However, the set mixes prefixes like agentlot_, standalone verbs like earn and me, and many semantically interchangeable verbs such as find, search, discover, rank, route, and list applied to similar objects.
With 124 tools, this is an extreme mismatch for a coherent server surface. Even for a broad marketplace, this many entry points creates severe navigation overhead and includes multiple generations of similar tools instead of a disciplined, minimal API.
The tool set broadly covers marketplace lifecycles: listings, requests, orders, delivery, disputes, payouts, projects, and assets. However, there are notable gaps such as updating/unpublishing listings, canceling/refunding orders, and other core lifecycle management operations that would be expected in a complete marketplace surface.