procure_outcomeTurn an outcome and budget into a planned AI/human/API/compute delivery chain. Planning does not spend automatically.
| Name | Required | Description | Default |
|---|---|---|---|
| roles | No | ||
| title | No | ||
| currency | No | ||
| objective | Yes | ||
| capability | No | ||
| budget_cents | Yes | ||
| worker_types | No | ||
| verification_type | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Given annotations are readOnlyHint=false and destructiveHint=false, the description adds valuable behavioral context by stating that planning does not spend automatically. This clarifies an important side-effect boundary beyond what the annotations communicate. However, it does not disclose other behavior such as whether a plan is persisted, returned, or requires subsequent approval, leaving some behavioral traits undisclosed.
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 focused sentences with no filler. The core transformation is stated first, and the critical behavioral caveat about spending is front-loaded and concise. Every sentence earns its place.
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 tool with 8 parameters, no output schema, and no parameter descriptions, this definition is too sparse to enable confident invocation. It gives a high-level concept but does not explain what the planned delivery chain looks like, how parameters interact, what happens after planning, or what output the agent should expect. The description is not complete enough for the tool's complexity.
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 0%, so the description must compensate. It maps 'outcome' to objective and 'budget' to budget_cents, which helps, but the remaining six parameters (roles, title, currency, capability, worker_types, verification_type) are left entirely unexplained. With 8 parameters and almost no parameter documentation, this is insufficient semantic support.
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 ('Turn') and resource ('an outcome and budget into a planned AI/human/API/compute delivery chain'), clearly stating what the tool accomplishes. The phrase 'Planning does not spend automatically' further distinguishes it from execution-focused siblings like execute_goal or do_goal. This is a clear, non-tautological purpose statement.
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 this tool is for planning rather than spending or execution, but it does not explicitly name alternatives or specify when to choose this over similar tools like plan_agent_team or plan_profitable_execution. 'Planned delivery chain' and 'does not spend automatically' provide context, but no exclusions or routing guidance. Usage is implied rather than explicit.
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.