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karlmehta
by karlmehta

trustmodel_trace_start

Initiate a new agent-trace capture session, returning a trace ID for logging steps and finalizing to create an evaluation run.

Instructions

Open a new agent-trace capture session. Returns a trace_id that must be passed to every trustmodel_trace_step and the final trustmodel_trace_finalize. Capture steps (thoughts, tool calls, tool results, responses) as your agent executes; finalize when done to upload + auto-create an evaluation run.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
goalYesWhat the agent is trying to achieve. Required; feeds the evaluation run.
nameYesDisplay name for the evaluation run (shown in TrustModel UI).
metadataNoFree-form passthrough metadata stored inside the trace file.
user_queryNoOriginal user prompt that triggered the run, if different from `goal`.
agent_modelNoUnderlying LLM the agent is using (e.g. 'gpt-4o', 'claude-sonnet-4-5').
agent_frameworkYesFramework the agent is built with (e.g. 'langchain', 'crewai', 'claude-code', 'custom').
expected_outcomeNoOptional description of the expected outcome.
Behavior4/5

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

With no annotations, the description carries full burden. It discloses that the tool returns a trace_id and outlines the capture session lifecycle, though it does not mention rate limits, errors, or auth needs.

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?

Two concise sentences with no wasted words, front-loaded with the primary action and outcome.

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?

The description covers the overall flow and return value, but without an output schema, some details about the trace_id are implied rather than explicit. Given the complexity, it is fairly complete.

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 coverage is 100%, so baseline 3 is appropriate. The description does not add meaning beyond the schema's detailed parameter descriptions.

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 clearly states the tool opens a new agent-trace capture session and returns a trace_id, distinguishing it from sibling tools like trustmodel_trace_step and trustmodel_trace_finalize.

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

Usage Guidelines5/5

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

The description explains the required sequence: use this tool to start, pass the trace_id to step and finalize, and finalize to upload. This provides clear context for when to use this tool versus alternatives.

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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