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BugSnag: List Trace Fields

bugsnag_list_trace_fields
Read-onlyIdempotent

Find available trace fields and custom attributes for filtering performance data. Identify metadata attached to spans to build dynamic, targeted filters.

Instructions

Get available trace fields/attributes for filtering

Toolset: Performance

Parameters:

  • projectId (string): Unique identifier of the project. This is optional if a current project is set and is used to set the current project for BugSnag tools.

Use Cases: 1. Find available custom attributes for performance filtering 2. Understand what metadata is attached to traces 3. Build dynamic filters based on available fields

Examples:

  1. Get all trace fields

{}

Expected Output: Array of field names and types available for filtering

Hints: 1. Trace fields are custom attributes added to spans 2. Use these fields for filtering other performance queries

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectIdNoUnique identifier of the project. This is optional if a current project is set and is used to set the current project for BugSnag tools.
Install Server

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds useful behavioral context by specifying the expected output as an array of field names and types and clarifying that trace fields are custom attributes added to spans. No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with sections and a front-loaded summary, making it scannable. However, it contains redundancy: the parameter bullet duplicates the schema, and the use cases and hints overlap with the opening sentence. It could be tighter without losing 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?

For a simple optional-parameter, read-only list tool with no output schema, the description covers the core purpose, usage scenarios, and expected output format. It is complete enough for an agent to select and call the tool correctly, though it does not discuss edge cases such as behavior when no project is set.

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%, and the description's Parameters section essentially restates the same projectId text already present in the schema. The description adds no new meaning about the parameter, so the baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with 'Get available trace fields/attributes for filtering', which names a specific verb and resource and states the purpose. It is distinguishable from sibling list tools because it targets trace fields specifically, though it does not explicitly contrast itself with alternatives like bugsnag_list_project_event_filters.

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?

Use Cases explicitly state when to use the tool: finding custom attributes for performance filtering, understanding trace metadata, and building dynamic filters. The Hints section reinforces that the returned fields should be reused in other performance queries, but it does not mention when not to use this tool or name an alternative.

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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