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Create Agent Eval Result

lyzr_create_agent_eval_result

Submit pass/fail results for an agent evaluation, including tested input, expected vs actual output, and status details for each case.

Instructions

Submit the results of running an agent evaluation (pass/fail outcomes per eval case).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agent_idYesAgent id being evaluated
agent_eval_idYesId of the agent eval config these results belong to
agent_eval_result_listYesList of eval results to record
Behavior3/5

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

Annotations already declare readOnlyHint=false, destructiveHint=false, and idempotentHint=false, so the description does not need to restate these. It adds no extra behavioral context such as whether the submit inserts or overwrites records, auth requirements, or side effects. The description is consistent with annotations, but adds only domain context.

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, front-loaded sentence with no redundancy. Every word contributes to explaining what the tool does, making it concise and easy to parse.

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?

Given the tool's moderate complexity (3 fully described parameters, annotations present, no output schema), the description is sufficient but leaves out some context such as return behavior or the prerequisite of an existing eval config. It is not incomplete enough to harm usage, but has room to add a bit more workflow context.

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%, with detailed descriptions for agent_id, agent_eval_id, and the structure of agent_eval_result_list. The description adds no parameter-specific details beyond the schema, so the baseline of 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 ('Submit') and clearly identifies the resource ('results of running an agent evaluation') with a scope ('pass/fail outcomes per eval case'). This distinguishes it from sibling tools like lyzr_create_agent_eval (which creates an eval config) and lyzr_get_agent_eval_result (which retrieves results).

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?

The phrase 'results of running an agent evaluation' gives clear context for when to use this tool: after an evaluation has been executed. It does not explicitly name alternatives or exclusions, but the intended workflow is implied, and the tool's relationship to related eval tools is understandable from the description.

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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