pix-mcp

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pix_get_gpu_timeline

Read-onlyIdempotent

Retrieve GPU queue execution scopes with actual GPU timings. Specify a queue ID or use the busiest queue, with optional time, limit, and stack filters for targeted analysis.

Instructions

One GPU queue's named scopes, as the GPU actually ran them.

The same shape as pix_get_thread_timeline but indexed by queue rather than thread, and the times are when the GPU executed the work rather than when the CPU submitted it. Without queue_id the busiest queue is used.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "capture_id": "<capture_id>"
    },
    "name": "pix_get_gpu_timeline"
  }
}

Input Schema

Name	Required	Description	Default
`limit`	No
`end_time`	No
`queue_id`	No
`capture_id`	Yes
`start_time`	No
`stack_level`	No
`cursor_position`	No
`timeout_seconds`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 9, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Annotations already mark the tool read-only and idempotent, and the description adds useful behavioral context beyond them: times are when the GPU executed work, output shape mirrors the thread timeline, and omitting queue_id selects the busiest queue. These are meaningful runtime behaviors not inferable from the schema or 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?

Three sentences, no repetition, with the core result stated first. Every sentence carries either definition or differentiation 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?

Given a read-only annotation set, an output schema, and a well-scoped description, the tool is largely callable without further investigation. The only gaps are semantics for several pagination/filter parameters and how to discover a specific queue_id, but the optional-busiest-queue default reduces the impact.

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?

With 0% schema description coverage, the description needed to compensate. It explains queue_id's default and reframes start/end as GPU execution time, but it does not describe limit, cursor_position, stack_level, timeout_seconds, or end_time semantics beyond their names.

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 states it returns one GPU queue's named scopes as actually executed, and explicitly contrasts it with pix_get_thread_timeline by queue indexing and GPU-execution timestamps. This clearly distinguishes it from the closest sibling without needing to inspect schema.

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?

It names the alternative pix_get_thread_timeline and gives the deciding criteria: queue vs thread and GPU-executed vs CPU-submitted time. It also documents the no-queue_id fallback to the busiest queue, so an agent knows when to call this tool directly.

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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