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serving_endpoints_query

Invoke a Databricks serving endpoint by sending a request to the model, supporting chat, completions, embeddings, or custom formats.

Instructions

Query/invoke a serving endpoint (POST /api/2.0/serving-endpoints/{name}/invocations).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesServing endpoint name
bodyYesRaw request body forwarded to the model. Shape depends on the underlying model (chat-completions, completions, embeddings, custom).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

Annotations indicate readOnlyHint=false, implying mutation. The description adds no behavioral context beyond that (e.g., that it sends data to the model, error handling, rate limits, idempotency). Minimal transparency.

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?

Very concise at two sentences, front-loading the purpose. No wasted words. Could be slightly expanded with usage hints, but still efficient.

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?

Description lacks context on how to construct the body for different model types (chat, completions, etc.), error handling, or response format. Output schema exists but is not referenced. Incomplete for the complexity of invoking models.

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% and parameter descriptions are provided. The description adds marginal value by noting the body shape depends on the underlying model. Meets baseline for high coverage.

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?

The description clearly states 'Query/invoke a serving endpoint' and provides the HTTP endpoint path, which distinguishes it from sibling tools like serving_endpoints_get (get config) and serving_endpoints_create (create endpoint). It specifies the verb and resource.

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

Usage Guidelines2/5

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

No guidance on when to use this tool vs. alternatives (e.g., serving_endpoints_get for configuration, serving_endpoints_list for listing). Does not mention appropriate contexts for invocation or prerequisites.

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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