reserve_computeCreate a bounded logical reservation. Paid compute requires prefunding and a configured hard cap; this call itself creates no external charge.
| Name | Required | Description | Default |
|---|---|---|---|
| job_id | No | ||
| asset_id | No | ||
| offer_id | No | ||
| funding_source | No | ||
| funding_reference | No | ||
| estimated_runtime_seconds | No | ||
| expected_settled_net_cents | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations indicate this is neither read-only nor destructive, and the description usefully adds that 'this call itself creates no external charge.' This clarifies a common concern about financial side effects. It does not fully explain what side effects do occur, but the annotation coverage plus the explicit no-charge note provides solid context.
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 sentences with no wasted words. The primary action is front-loaded, and the caveat about external charges earns its place because it preempts a likely behavioral concern. Length is appropriate for the content provided.
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?
With seven parameters, no required fields, no output schema, and no sibling differentiation, the description is too thin. It does not explain what a 'logical reservation' means, what the return value is, how to choose fields, or what happens after the call. An agent would struggle to construct a correct invocation from this description alone.
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 for the seven undocumented parameters. It makes a passing reference to 'prefunding' and 'hard cap,' which loosely relates to funding_source and expected_settled_net_cents, but it does not explain job_id, asset_id, offer_id, funding_reference, estimated_runtime_seconds, or expected_settled_net_cents. The description leaves most parameter semantics unexplained.
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 specific action and resource: 'Create a bounded logical reservation.' This is clear enough to distinguish the tool from compute-related siblings like quote_compute or compute_status. However, the phrase 'bounded logical reservation' is somewhat jargony and doesn't precisely define what a reservation entails.
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 gives a clear precondition—'Paid compute requires prefunding and a configured hard cap'—which implies when the tool is appropriate. But it does not explicitly state when to use this tool versus alternatives, nor does it mention any sibling tool or exclusion criteria. Usage context is implied rather than direct.
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.
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.