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Create World Model Evaluation Run

lyzr_world_model_create_evaluation_run

Create an evaluation run to test an agent against a World Model's test cases, tracking progress, metrics, and outcomes.

Instructions

Create a new evaluation run for an agent against a World Model's test cases.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusNoInitial run status (default handled server-side)
agent_idYesThe agent id being evaluated
run_nameYesA human-readable name for this evaluation run
agent_nameYesThe agent's display name
is_runningNoWhether the run is currently in progress
duration_msNoRun duration in milliseconds
world_model_idYesThe World Model id being evaluated against
overall_progressNoOverall progress percentage
selected_metricsNoMetric names to evaluate for this run
total_test_casesNoTotal number of test cases in the run
failed_test_casesNoNumber of failed test cases
pending_test_casesNoNumber of pending test cases
running_test_casesNoNumber of currently running test cases
completed_test_casesNoNumber of completed test cases
Behavior2/5

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

Annotations already declare the tool is non-read-only and non-idempotent, but the description adds no behavioral details such as whether the run starts immediately, whether it is asynchronous, or how progress is tracked. There is no contradiction with annotations, but no extra transparency value beyond them.

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 a single sentence that front-loads the verb and resource, contains no filler, and communicates the core purpose immediately.

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

Completeness3/5

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

For a creation tool with 14 parameters and no output schema, the description only provides the core purpose and does not mention return values or post-creation monitoring via sibling tools like lyzr_world_model_get_evaluation_run. However, the schema fully documents parameters and annotations clarify the mutating nature, making it minimally adequate.

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 all 14 parameters and their meanings. The description adds no additional parameter-level context, defaults, or relationships, so the baseline 3 applies.

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 uses a specific verb ('Create') and clear resource ('evaluation run') with context ('for an agent against a World Model's test cases'). It distinguishes this creation operation from sibling list/get evaluation run tools and other world model tools.

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?

The description gives no explicit guidance on when to use this tool versus alternatives like lyzr_create_agent_eval or lyzr_world_model_list_evaluation_runs. The 'for an agent against a World Model's test cases' phrasing implies the use case but does not explain exclusions or follow-up steps.

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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