Get the current earnings + payout snapshot for the authenticated creator: held_cents, payable_cents, is_claimed, kyc_status, payout_blocked(+reason), cap_cents, used_cents, and remaining_cents (cap headroom; null when uncapped). This is a point-in-time snapshot, not a time series.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark this as read-only, idempotent, and non-destructive, so the description does not need to re-disclose those traits. It adds genuine behavioral context: authentication scoping, point-in-time semantics, the payout_blocked/reason detail, and the edge case of remaining_cents being null when uncapped. No contradiction exists with the annotations.
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?
Two sentences of high-density, useful information; every clause earns its place. The primary purpose is front-loaded, and the second sentence adds a meaningful scope limiter without repetition.
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?
Without an output schema, the description generously details the returned fields, their semantics, and a null edge case, which is enough for an agent to understand what it will receive. It does not spell out response formatting or error behaviors, but for a read-only, parameterless tool the available context is nearly complete.
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?
There are zero parameters, so there is nothing for the description to add beyond the existing schema. The description implicitly confirms this by focusing entirely on the return snapshot and its meaning rather than inputs. This matches the baseline for a parameterless tool.
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 names a specific action ('Get'), a resource ('current earnings + payout snapshot for the authenticated creator'), and enumerates the exact fields returned. This clearly distinguishes it from sibling tools like get_post_performance and get_profile, and the final sentence helps differentiate it from any potential time-series reporting tool.
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?
The phrase 'for the authenticated creator' makes the intended scope clear, and 'point-in-time snapshot, not a time series' provides an explicit exclusion for trend-querying use cases. There is no near-sibling earnings-based tool to explicitly contrast with, so the guidance is strong but not exhaustive.
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.
Most tools clearly target distinct resources and actions, but there is some overlap: get_profile and get_my_earnings both expose balance/cap information, and list_my_profiles could be confused with get_profile. The descriptions are generally clear enough to avoid serious misselection.
Every tool name follows a consistent snake_case verb_noun pattern: get_product, list_campaigns, submit_post, update_profile, etc. The verbs match the intended actions, and there are no mixed naming conventions or vague style deviations.
Twenty tools is slightly heavy, but the count is reasonable for the scope: the server covers products, campaigns, posts, earnings, profiles, notifications, asset uploads, and AI tool usage/reviews. Each tool serves a recognizable purpose, so the size feels like breadth rather than redundancy.
Core workflows are present—search products, get campaigns, apply, generate tracking links, submit posts, view earnings, manage notifications—but there are notable gaps. There is no way to list past posts or retrieve a post_id except from submit_post, no list of campaign applications, and no tool discovery endpoint for the AI tool slugs used by declare_tool_usage and write_tool_review.
