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tracelens-analysis-orchestrator

Orchestrates modular PyTorch profiler trace analysis with TraceLens: generates perf reports, prepares category data, runs system-level and compute-kernel…

Skill by amd

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Install

Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/amd-tracelens-analysis-orchestrator

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About

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.

Use cases: documents, data, ml, productivity

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Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
No tools found
Secrets
None asked for
Install scripts
None found
Runs as
Python package

Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/tracelens-analysis-orchestrator

What's inside

Skill 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
Instructions
46 lines in SKILL.md · view on GitHub

Before installing

  • Ships executable scripts

Files (55)

  • .federated.json
  • SKILL.md
  • convolution-analyzer.md · agents/
  • cpu-idle-analyzer.md · agents/
  • elementwise-analyzer.md · agents/
  • gemm-analyzer.md · agents/
  • generic-op-analyzer.md · agents/
  • kernel-coherence-agent.md · agents/
  • kernel-fusion-analyzer.md · agents/
  • kernel-stem-preprocessing-agent.md · agents/
  • kernel-unification-agent.md · agents/
  • model-identification-agent.md · agents/
  • moe-analyzer.md · agents/
  • multi-kernel-analyzer.md · agents/
  • norm-analyzer.md · agents/
  • reduce-analyzer.md · agents/
  • sdpa-analyzer.md · agents/
  • semantic-comparison-agent.md · agents/
  • triton-analyzer.md · agents/
  • .gitignore · evals/
  • EVAL_RUBRICS.md · evals/
  • README.md · evals/
  • combined_traces_comparative.csv · evals/analysis_tests/
  • combined_traces_standalone.csv · evals/analysis_tests/
  • generate_ref.sh · evals/eval_scripts/
  • kill_eval_jobs.sh · evals/eval_scripts/
  • pack_test_archives.sh · evals/eval_scripts/
  • run_pi_analysis_in_docker.sh · evals/eval_scripts/
  • run_repeatability_parallel.sh · evals/eval_scripts/
  • aggregate_repeatability.py · evals/eval_utils/
  • compare_lca_partitions.py · evals/eval_utils/
  • manual_eval_checklist.md · evals/eval_utils/
  • merge_results.py · evals/eval_utils/
  • quality_scripted_evals.py · evals/eval_utils/
  • report_section_rules.yaml · evals/eval_utils/
  • workflow_scripted_evals.py · evals/eval_utils/
  • evals.json · evals/
  • machine.yml · evals/
  • README.md · evals/partial_tests/
  • semantic_partition_scripted_evals.py · evals/partial_tests/eval_utils/
  • semantic_purity_aggregate.py · evals/partial_tests/eval_utils/
  • generate_gold_ref.sh · evals/partial_tests/
  • partial_test_cases.csv · evals/partial_tests/
  • run_partial_tests.sh · evals/partial_tests/
  • SKILL.md · evals/skills/eval-post-processing/
  • reference.md · evals/skills/eval-post-processing/
  • run_post_processing.py · evals/skills/eval-post-processing/
  • SKILL.md · evals/skills/quality-llm-eval/
  • reference.md · evals/skills/quality-llm-eval/
  • SKILL.md · evals/skills/workflow-llm-eval/
  • reference.md · evals/skills/workflow-llm-eval/
  • reference.md
  • skill-card.md
  • analysis_template.md · templates/
  • sub_agent_spec.md · templates/

SKILL.md (first lines)

<!--
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, and plot embedding).

## Workflow index

```
0. Query User Inputs (interactive answers or a run YAML, Environment Setup) → cache/run_config.yaml
1. Generate Performance Report (one wrapper call on cache/run_config.yaml; semantic pre-processing first)
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`.

From amd/skills, MIT.

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    tracelens-analysis-orchestrator skill. Agent Mart. https://agentmart.dev/skills/amd-tracelens-analysis-orchestrator (last updated 2026-10-24)