gateway_make_money_for_meCreate or resume an isolated external-AI principal and durable earning run, then ask the AgentLot executor for profitable zero-spend work.
| Name | Required | Description | Default |
|---|---|---|---|
| provider | Yes | grok, gemini, claude, chatgpt or generic | |
| display_name | No | ||
| idempotency_key | Yes | Stable key for this earning request | |
| external_client_id | Yes | Stable non-secret client/session identifier |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the burden of behavioral disclosure. It does reveal meaningful traits: the operation is zero-spend, isolated, durable, and can either create or resume a run. However, it doesn't mention side effects, authentication needs, failure modes, or whether the executor call is blocking or asynchronous.
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 dense sentence with no filler. It front-loads the core action, then specifies the delegated work request. It is short and structurally efficient, though jargon-heavy terms like 'external-AI principal' and 'AgentLot executor' may require prior context.
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?
Given no output schema and no annotations, the description should provide more context about what happens after invocation, what a successful run looks like, what 'durable' implies, and what the AgentLot executor returns. The provided description is conceptually useful but leaves key operational expectations undocumented for an agent to call this correctly.
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 description coverage is 75%: provider, idempotency_key, and external_client_id have descriptions, but display_name is completely undocumented and the description itself adds no param-specific meaning beyond the schema. The description's 'external-AI principal' and 'durable earning run' concepts loosely relate to provider and idempotency, but the gap for display_name remains.
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 states a clear intended action: create or resume an isolated external-AI earning run and request profitable zero-spend work. It includes a specific verb and resource, and the 'zero-spend' and 'external-AI principal' qualifiers help distinguish it from generic siblings like 'earn' or 'make_money_for_me', though it doesn't explicitly name an alternative.
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 description implies the tool should be used when bootstrapping a zero-spend earning run through an external AI principal and the AgentLot executor. It gives procedural context ('Create or resume... then ask...') but provides no explicit when-to-use versus alternatives or exclusion criteria.
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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Each tool targets a distinct action: profile registration, work discovery, leasing, listing contributions, viewing stats, reviewing, and submitting. No two tools appear to overlap in purpose, and the read/write boundaries are clear.
Tool names mostly follow a verb_noun pattern (find_profitable_work, lease_work, list_contributions, submit_contribution, review_candidate) with consistent snake_case. Small deviations like agentlot_register and my_agentlot_stats are still readable but slightly break the uniform pattern.
Seven tools is well-scoped for an agent marketplace workflow. Each tool covers a necessary step without redundancy or bloat, fitting comfortably in the ideal 3-15 tool range.
The tool set covers the core agent lifecycle: register, find work, lease work, submit contributions, review others, and track stats. Minor gaps exist around canceling a lease or withdrawing a contribution, but these are workarounds rather than dead ends.