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kvrancic

prime-intellect-mcp

by kvrancic

pod_quote

Get a non-binding price quote and reserved provisioning token for a GPU pod. Use the token to confirm and provision within 60 seconds.

Instructions

Get a non-binding price quote + reserved provisioning payload.

Returns a quote_token (TTL=60s) that you pass to pod_create with confirm=True to actually provision. This tool has NO side effects.

The server picks the cheapest matching GPUAvailability row that satisfies the requested disk/vcpu/memory. If none matches, returns an error explaining what's available.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
gpu_typeYesGPU type slug, e.g. 'H100_80GB'.
gpu_countNoNumber of GPUs per pod (1, 2, 4, 8).
disk_size_gbNoDisk size in GB.
vcpusNovCPU count.
memory_gbNoMemory in GB.
imageNoContainer image slug. Use 'ubuntu_22_cuda_12' if unsure.ubuntu_22_cuda_12

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, description carries full behavioral burden. It discloses no side effects, TTL of 60s, server picks cheapest matching row, and returns error with available options if no match. Comprehensive and honest.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Four sentences with front-loaded purpose, then flow, behavior, and error case. No fluff, every sentence adds value. Very concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity and presence of output schema, the description covers essential aspects: return value, TTL, side-effect-free nature, selection logic, and error behavior. Complete for a quoting tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents each parameter well. Description adds overall logic (cheapest matching) but no extra per-parameter meaning beyond schema defaults and examples.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the tool gets a non-binding price quote and reserved provisioning payload, distinguishing it from sibling tools like pod_create. It specifies the verb 'Get' and the resource, making purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Description explains that the tool has no side effects and that the returned quote_token should be passed to pod_create with confirm=True to provision. It implicitly guides usage before creation, but lacks explicit when-not-to-use or alternatives.

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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