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karlmehta
by karlmehta

trustmodel_trace_finalize

Close an active trace session, upload captured steps to cloud, and auto-create an agentic evaluation run. Returns file path and evaluation run ID.

Instructions

Close an active trace session, serialize the captured steps, upload to TrustModel cloud storage, and auto-create an agentic evaluation run. Returns both a file_path (for record-keeping / retry) and an evaluation_run_id that can be polled with trustmodel_score_agent.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
goalNoOverride `goal` if the agent learned more at runtime.
nameNoOverride `name` provided at trace_start.
successNoWhether the run is considered successful overall.
trace_idYesTrace handle returned by trustmodel_trace_start.
agent_modelNoOverride `agent_model` provided at trace_start.
goal_achievedNoWhether the agent achieved its goal.
actual_outcomeNoOptional description of what actually happened.
final_responseNoThe final user-facing answer from the agent.
agent_frameworkNoOverride `agent_framework` provided at trace_start.
expected_outcomeNoOverride `expected_outcome` provided at trace_start.
total_duration_msNoTotal execution time in ms. If omitted, computed from step durations.
Behavior3/5

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

The description states that the active trace session is closed and an evaluation run is auto-created, implying irreversibility. However, it does not disclose side effects like whether data can be overwritten, any rate limits, or whether finalization can be repeated. Since no annotations are provided, the description should be more thorough.

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 core action and lists subsequent steps efficiently. No wasted words or redundancy.

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 complexity (11 parameters, no output schema, no annotations), the description covers the main workflow and return values. It mentions how to use evaluation_run_id. However, it could be more complete by explicitly stating prerequisites (e.g., trace must be started) and explaining what 'agentic evaluation run' means. The schema handles parameter details well.

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?

The input schema has 100% description coverage, so each parameter is already explained. The tool description does not add further meaning to the parameters but provides context for return values (file_path and evaluation_run_id). Per guidelines, baseline is 3 when schema coverage is high.

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 specific verbs (close, serialize, upload, auto-create) and clearly identifies the resource (active trace session). It distinguishes itself from sibling tools like trustmodel_trace_start (opens session) and trustmodel_trace_step (logs steps), making its purpose unambiguous.

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?

The description implies the tool should be used after starting a trace (since it closes an active session) and mentions polling with trustmodel_score_agent, but it does not provide explicit guidance on when to choose this tool over alternatives like trustmodel_evaluate_local or trustmodel_govern. Lacks explicit usage conditions.

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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