tracelens-analysis-orchestrator — Claude Code skill: PyTorch trace
A skill that runs the agentic TraceLens workflow over PyTorch Profiler traces and writes a prioritized analysis.md.
npx skills add amd/skills --skill tracelens-analysis-orchestrator -a claude-codeWhat tracelens-analysis-orchestrator does
The skill lays out the whole pipeline. It starts by asking for the platform, trace path, analysis mode (training or inference) and environment setup, then generates a performance report and runs a trace-quality gate. If the trace fails that gate, a deterministic fallback analysis takes over. Category data comes next: GPU utilization, top ops, tree data, multi-kernel data.
Analysis splits into two parallel tracks. System-level work covers CPU and idle time, kernel fusion, collective communication and memcpy, writing into system_findings/. Separate subagents handle compute kernels — GEMM, SDPA, elementwise — and write into category_findings/. The orchestrator runs everything else itself, including aggregating findings into priority_data.json.
Subagents are launched only where the procedure calls for them: the Task tool in Claude and Cursor, spawn_agent under Codex. Steps 7, 8 and 10 are the only ones that need a subagent primitive; the rest goes through the command prefix in <output_dir>/cache/cmd_prefix.txt. The deliverable is <output_dir>/analysis.md.
What it helps with
- analyze a single PyTorch Profiler trace and get a prioritized report
- compare two traces side by side
- separate system-level bottlenecks from slow compute kernels
- check trace quality before trusting the numbers
- merge subagent findings into one
analysis.md
Example prompts for the agent
- analyze
profile.pt.trace.jsonwith the analysis orchestrator - compare
run_a.jsonandrun_b.jsonin training mode - run the agentic trace analysis and produce
analysis.md
How to install tracelens-analysis-orchestrator
1Skills CLI (Vercel)
npx skills add amd/skills --skill tracelens-analysis-orchestrator -a claude-code2Manually: put the files in place
~/.claude/skills/tracelens-analysis-orchestrator/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/tracelens-analysis-orchestrator/
1Skills CLI (Vercel)
npx skills add amd/skills --skill tracelens-analysis-orchestrator -a codex2Manually: put the files in place
.agents/skills/tracelens-analysis-orchestrator/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add amd/skills --skill tracelens-analysis-orchestrator -a cursor2Manually: put the files in place
.cursor/skills/tracelens-analysis-orchestrator/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install amd/skills tracelens-analysis-orchestrator2Manually: put the files in place
.github/skills/tracelens-analysis-orchestrator/SKILL.md1Skills CLI (Vercel)
npx skills add amd/skills --skill tracelens-analysis-orchestrator -a gemini-cli2Platform CLI
gemini skills install https://github.com/amd/skills --path skills/tracelens-analysis-orchestratorManually: put the files in place
.devin/skills/tracelens-analysis-orchestrator/SKILL.mdThe legacy .windsurf/skills/ path still works
Skills CLI (Vercel)
npx skills add amd/skills --skill tracelens-analysis-orchestrator -a opencodeClaude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
Step by step, with commands for each platform: How to install skills in Claude Code: five ways
Questions about tracelens-analysis-orchestrator
How do I install tracelens-analysis-orchestrator in Claude?
Run npx skills add amd/skills --skill tracelens-analysis-orchestrator -a claude-code. The skill lands at ~/.claude/skills/tracelens-analysis-orchestrator/SKILL.md.
What does tracelens-analysis-orchestrator do?
It orchestrates PyTorch Profiler trace analysis with TraceLens: generates a perf report, prepares category data, runs system-level and compute-kernel subagents in parallel, and writes analysis.md.
What do I need to run the subagents?
Your runner's subagent primitive — the Task tool in Claude and Cursor, spawn_agent under Claude. It is used only in steps 7, 8 and 10; the orchestrator handles the rest.
Source text
SKILL.md · MIT
---
name: tracelens-analysis-orchestrator
description: >-
Orchestrates modular PyTorch profiler trace analysis with TraceLens: generates perf
reports, prepares category data, runs system-level and compute-kernel subagents in
parallel, validates outputs, and writes a prioritized stakeholder report (analysis.md).
Use when the user asks to follow the analysis orchestrator, run the agentic analysis
workflow, analyze a trace, compare two traces, or mentions standalone or comparative
TraceLens analysis.
license: MIT
---
<!--
Copyright (c) 2026 Advanced Micro Devices, Inc. All rights reserved.
See LICENSE for license information.
-->
# Analysis orchestrator
Coordinate **system-level** analysis (CPU/idle, kernel fusion, multi-kernel / comm / memcpy) and **compute-kernel** analysis (GEMM, SDPA, elementwise, etc.): one trace load, shared prep, parallel subagents, then aggregation into `analysis.md`.
## Full procedure
Follow **[reference.md](reference.md)** for every step (user prompts, `<prefix>` / `{CMD}` usage, CLI commands, subagent launch text, validation, report `tee` order, plot embedding, and trace diagnostics).
## Workflow index
```
0. Query User Inputs (Platform, Trace Path(s), Analysis Mode, Environment Setup)
1. Generate Performance Report (branches on analysis mode: training vs inference then, comparison scope)
2. Trace-Quality Gate → Deterministic fallback analysis
3-6. Prepare Category Data (GPU Util, Top Ops, Tree Data, Multi-Kernel Data, Category Filtering)
7. System-Level Analysis (PARALLEL) → system_findings/
8. Compute Kernel Subagents (PARALLEL) → category_findings/
8.5. Aggregate → priority_data.json::findings[]
9. Validate Subagent Outputs
10. load_findings + Model Identification (subagent) → metadata/model_info.json
11. Render performance PNG if agent_extension.py is absent
12. Generate analysis.md (orchestrator writes via <prefix> tee), optional extension, embed PNG
```
## Rules
- **Subagents:** Use your runner's subagent primitive (the Task tool in Claude Code or Cursor, `spawn_agent` under Codex) **only** where reference.md says “subagent” (Steps **7**, **8**, **10**). The orchestrator runs everything else, including Step 8.5, using the command prefix from `<output_dir>/cache/cmd_prefix.txt` (`{CMD}` substitution).
- **Language:** Prefer vendor-agnostic terms (GPU kernels, collective communication, vendor GEMM library, DNN primitives, GPU graph). When quoting trace data, real kernel names are fine.
- **Subagent prompts:** Point each subagent at the checked-in agent file under `TraceLens/Agent/Analysis/skills/analysis-orchestrator/agents/<name>.md` (see reference.md for exact paths and prompt shells).
## Primary outputs
- **Deliverable:** `<output_dir>/analysis.md`
- **Internals:** `system_findings/`, `category_findings/`, `category_data/`, `metadata/`, `perf_report*.xlsx`, CSV folders — see package README for layout.
## Agent layout
Project subagents ship with this skill: `TraceLens/Agent/Analysis/skills/analysis-orchestrator/agents/*.md`.
© amd · MIT · amd/skills