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trace_create

Create an execution trace to audit multi-step agent workflows. Start a trace, add steps as the operation proceeds, then complete it for a full record.

Instructions

Create an execution trace to track a multi-step agent workflow.

Start a trace before a complex operation, add steps as you go, then complete it. Traces provide a full audit of agent reasoning.

Args: name: Name describing this trace (e.g. "research-and-summarize"). metadata: Optional JSON string with additional metadata.

Returns: JSON string with trace_id and status.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
metadataNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

The description discloses that the tool creates a trace and returns a trace_id and status, but lacks details on persistence, limits, or side effects. The annotation destructiveHint=false is consistent, but the description adds minimal behavioral context beyond what is implicit.

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 with five sentences, no redundancy, and a logical flow: purpose, usage workflow, parameter explanations, return value. Every sentence adds value.

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 essential aspects: creation, lifecycle, parameters, and return format. It mentions trace_id needed for subsequent steps, which aids completeness. Minor omission: no mention of error handling or limits.

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

Parameters4/5

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

The description adds value over the bare schema by explaining the 'name' parameter as a descriptive label with an example, and 'metadata' as an optional JSON string. Given 0% schema coverage, this compensation is adequate but could be more precise about metadata format.

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 creates an execution trace for multi-step workflows. It distinguishes from sibling tools like trace_complete and trace_step by specifying it is the start of the trace lifecycle.

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 description advises to start a trace before complex operations, then add steps and complete it, providing clear context for usage. It implicitly differentiates from trace_step and trace_complete but does not explicitly state when not to use.

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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