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together-ai

List evaluation jobs

together_list_evaluations
Read-only

List LLM-as-a-judge evaluation jobs (classify, score, compare) with status, parameters and results once completed. Together: GET /evaluation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of jobs to return.
statusNoFilter by status: pending, queued, running, completed, error, user_error.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, covering the safety profile. The description adds useful context that results only appear 'once completed' and that jobs carry parameters, but says nothing about pagination, ordering, or result volume, so it adds modest value beyond the annotation.

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?

Two tightly packed sentences, with the core purpose and return content front-loaded and the API route tacked on last. Nothing is wasted, though the endpoint reference is not strictly necessary for invocation.

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

Completeness4/5

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

For a simple two-parameter read-only list tool with no output schema, the description covers purpose, filterable status semantics, and return content adequately. An agent has enough to call it correctly, with only minor gaps around pagination and ordering.

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% and both parameters (limit, status) are fully documented, so the schema does the heavy lifting. The description nods at 'status' as a filter dimension but adds no syntax or default-behavior detail beyond the schema, matching the baseline.

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

Purpose4/5

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

The description gives a specific verb (List) and resource (LLM-as-a-judge evaluation jobs), and even enumerates the subtypes (classify, score, compare) plus what each job carries (status, parameters, results). No sibling is a plausible confusion for this resource, so the lack of an explicit contrast is not costly.

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

Usage Guidelines3/5

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

Usage is implied by the verb and the read-only listing scope, but the description never states when to reach for this tool versus alternatives, nor any prerequisite such as needing completed jobs to see results. It leaves the agent to infer the call context.

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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