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Okareo MCP Server

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by okareo-ai

Re-evaluate Test Run

reevaluate_test_run

Re-score a finished test run against updated or additional checks without re-executing the model. Apply changed check definitions or new evaluation criteria to existing results.

Instructions

Re-score a completed test run against a set of checks.

    Re-runs checks against an already-finished test run without re-executing
    the original model or simulation, and without changing the original
    run's results. Useful after a check definition changed, or to score an
    existing run against additional checks.

    Args:
        test_run_id: UUID or name of a completed test run.
        checks: Optional list of check names (or IDs) to score against.
            When omitted, the run's existing checks are re-run.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
checksNo
test_run_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Discloses that it does not re-execute the original simulation and does not change original run results, adding valuable context beyond the annotations. It does not mention idempotency or other side effects, but the output schema covers return behavior, and the annotation openWorldHint already signals possible side effects.

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?

The description is concise, front-loaded with the main purpose, and includes a structured Args list. Every sentence adds value, making it easy to scan and understand quickly.

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?

With an output schema present, the description does not need to explain return values. Prerequisites, use cases, and parameter semantics are all clearly covered, so the tool can be invoked correctly without further information.

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

Parameters5/5

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

Schema has zero parameter descriptions, yet the description fully explains both parameters: test_run_id is a UUID/name of a completed run, and checks is an optional list with clear behavior when omitted. This completely compensates for the schema gap.

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 it re-scores a completed test run without re-executing the model/simulation, distinguishing it from run_test and get_test_run_results. The verb 're-score' plus the qualifier 'without re-executing' provides precise scope and uniqueness.

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?

Explicitly notes it is useful after a check definition changed or to score against additional checks, giving clear when-to-use context. However, it does not explicitly name alternative tools or state when not to use this tool, so it stops short of full guidance.

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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