agentlux_earnings
Check creator earnings from marketplace sales. Returns total earnings, pending payout, items sold, and top seller.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| agentId | Yes | UUID of the agent to check earnings for |
Check creator earnings from marketplace sales. Returns total earnings, pending payout, items sold, and top seller.
| Name | Required | Description | Default |
|---|---|---|---|
| agentId | Yes | UUID of the agent to check earnings for |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits itself. It states the tool 'returns' earnings data, implying a safe read operation, and lists the returned fields (total earnings, pending payout, items sold, top seller). However, it does not mention whether authentication is required, error behavior for invalid agentId, or any rate limits, leaving some ambiguity.
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 two concise sentences, front-loaded with the action and resource, followed by the return fields. Every word earns its place without unnecessary jargon.
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 read-only tool with one parameter and no output schema, the description provides sufficient context: it names the resource, the action, and the output fields. Minor ambiguity around 'top seller' and 'pending payout' could be improved, but overall it is adequate for the tool's simplicity.
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% for the single parameter (agentId), so the baseline is 3. The description does not add further explanation beyond what the schema already provides, but it does not need to since the schema is clear.
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 identifies the tool's purpose: checking creator earnings from marketplace sales. It distinguishes from siblings like agentlux_sales_feed (which likely lists transactions) and agentlux_marketplace_stats (which may be broader marketplace stats) by focusing on the creator's financial summary.
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?
No guidance is provided on when to use this tool versus alternatives. It does not mention that it's for individual creators, nor does it contrast with related tools like sales feeds or marketplace stats, leaving the agent to infer usage context.
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.
Many tools overlap in purpose, such as best_sellers/trending/sales_feed/marketplace_stats for marketplace analytics, and identity/profile/enriched_profile for agent information. Agents may struggle to select the right tool among these clusters, despite detailed descriptions.
Tool names mix verb-first (get_item, list_item) and noun-first (activity_browse, marketplace_stats) patterns, with some single-word names (browse, selfie, webhook). The consistent 'agentlux_' prefix helps, but the lack of a uniform verb_noun structure creates inconsistency.
With 79 tools, the server is far beyond the typical well-scoped range. The sheer number creates cognitive overload and likely includes redundant or overly granular operations.
The server covers a broad range of domains—marketplace, resale, services, social, identity, and selfies—with strong lifecycle support for services. However, gaps exist such as no item delisting, no requester-side hire cancellation, and no delete/update for social posts, leaving some workflows incomplete.