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scarletfantasy

nsight-graphics-mcp

List GPU Trace metrics

list_gpu_trace_metrics
Read-onlyIdempotent

Retrieve and page through all GPU Trace metrics for a full frame or marker range, preserving raw Nsight values and adding display groups and units.

Instructions

Page through every exported GPU Trace metric for the full frame or a marker range. Metrics preserve their raw Nsight names and numeric values and add inferred display groups and units.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNo
groupNo
limitNo
offsetNo
sort_byNoname
range_idNoMarker range id returned by list_gpu_trace_ranges.
report_idYesGPU Trace report session id returned by collect_gpu_trace_report or open_gpu_trace_export.
name_regexNo
Install Server

TDQS

A4/5.0
Behavior4/5

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

Beyond the annotations (readOnly, idempotent, not destructive), the description adds useful behavioral context: it mentions pagination ('page through') and that metrics 'preserve their raw Nsight names and numeric values' while adding 'inferred display groups and units'. This explains behavior not already captured by annotations.

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 two sentences, front-loaded with the core action. Every sentence adds value: the first states the purpose, the second details the output characteristics. No filler or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 8 parameters and no output schema, the description provides a decent high-level overview but does not mention return structure or pagination details. It is adequate for tool selection but not for full invocation understanding, especially since sibling tools are similar.

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

Parameters2/5

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

Schema description coverage is only 25% (only report_id and range_id have descriptions). The description mentions 'marker range' implicitly referencing range_id but does not explain kind, sort_by, limit, offset, group, or name_regex. With such low schema coverage, the description should compensate but does not.

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 explicitly states 'Page through every exported GPU Trace metric for the full frame or a marker range', which clearly identifies the action (page through list), the resource (GPU Trace metrics), and the scope (full frame or marker range). It also distinguishes this from sibling tools like list_gpu_trace_timeline_events by focusing on metrics.

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 provides clear context on when to use the tool: when you need all exported GPU Trace metrics for a full frame or a marker range. It does not explicitly exclude alternatives or name a more specific tool, but the context is sufficient for basic selection.

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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