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spraay_bittensor_chat_completions

Send chat completion requests to Bittensor AI models. Pay $0.03 USDC per call, no API keys required.

Instructions

Bittensor inference. Costs $0.03 USDC per call. Provide the listed fields as typed arguments.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelYesmodel parameter
messagesYesmessages parameter
max_tokensNomax_tokens parameter
temperatureNotemperature parameter

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYesTrue when the gateway call succeeded; false when it returned an error.
dataNoThe gateway response payload on success. The exact shape depends on the tool (see the tool description and the JSON in the text content block).
errorNoHuman-readable error message, present only when ok is false.
Behavior2/5

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

Annotations are present but the description adds only the cost ($0.03 USDC per call). No other behavioral traits like permissions, rate limits, or error handling are disclosed. The 'openWorldHint' annotation suggests the tool may have side effects beyond the obvious, but the description does not elaborate.

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

Conciseness4/5

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

The description is concise at two sentences, front-loaded with the purpose. However, it could be more structured with dedicated sections. No wasted words.

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

Completeness2/5

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

Given the tool's complexity (4 parameters, 2 required, output schema exists), the description is very incomplete. It does not explain the expected format of messages, the role of model, or the effect of optional parameters. Costs are mentioned but no further context about the inference behavior.

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 coverage is 100% with parameter descriptions, but they are tautological ('model parameter', 'messages parameter'). The description adds 'Provide the listed fields as typed arguments' which adds no semantics. Baseline 3 is appropriate as the description neither enhances nor harms parameter understanding.

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

Purpose3/5

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

The description states 'Bittensor inference' which gives a general idea but lacks specificity. It does not explicitly mention chat completions or differentiate from sibling tools like spraay_bittensor_embeddings. The name provides some clarity, but the description must stand alone.

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

Usage Guidelines1/5

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

No guidance on when to use this tool versus alternatives. It does not mention prerequisites, context, or when to avoid this tool. Users are left to infer from the name alone.

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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