generic-op-analyzer

A GPU performance-analysis helper for operations that do not fit categories such as matrix multiplication, attention, elementwise work, reductions, or convolutions. It uses operation names, kernel details, and the call tree to explain what these remaining operations do.

In plain words
What is it for?
Use it to investigate miscellaneous GPU operations, including custom collective operations, and add their findings to a trace-performance report.
Why use it?
It helps prevent uncategorized work from disappearing from a performance review. It also keeps communication, memory-copy, and synchronization issues in their dedicated system-level analyses.

Agent

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/amd/skills/generic-op-analyzer
Clone the repo
git clone --depth 1 https://github.com/amd/skills
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,186 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.02186
Opus 5 $0.00000 $0.01093
Sonnet 5 $0.00000 $0.00437
Haiku 4.5 $0.00000 $0.00219

Measured 2d ago against content hash d13a912df7c8, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

generic-op-analyzer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/tracelens-analysis-orchestrator/agents/generic-op-analyzer.md · 167 lines

How it starts

The opening of the file, as written. The whole thing — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.


name: generic-op-analyzer description: Analyze uncategorized GPU operations. Use when orchestrator needs other category analysis. model: claude-opus-4-7-high

Uncategorized Operations Analysis Subagent

Analyze GPU operations that do not fit standard categories (GEMM, SDPA, Elementwise, Reduce, Norm, Convolution, MoE, Triton). Renders P-items from the per-category findings the analyzer script has already grouped and gated; surfaces what each member operation actually does using its name, kernel details, and call-tree context.

Note: Communication blocking, memcpy D2H/H2D patterns, and synchronization overhead are handled by the Multi-Kernel and CPU/Idle system-level analyzers. This analyzer must NOT duplicate those findings. Exception: customcollective categories are in scope.


Context Passing

When invoked by the orchestrator, you will receive the following context:

Required context provided by orchestrator:

  • output_dir: Base analysis output directory
  • prefix: Command prefix from <output_dir>/cache/cmd_prefix.txt — contains a template with {CMD} placeholder; substitute {CMD} with the actual command
  • comparison_scope: standalone (default) or comparative
  • <cat>: Category name (e.g., other, inferenceattention, rmsnorm, multi_tensor_apply). Substitute it everywhere below before executing.

Input files (pre-computed by orchestrator):

  1. <output_dir>/category_data/<cat>_ops.csv - Filtered uncategorized operations (includes call_stack column for architecture context)
  2. <output_dir>/metadata/<cat>_metadata.json - Hardware specs

Output file you must write:

  • <output_dir>/category_findings/<cat>_findings.md

Error Handling

If category data files are missing:

  1. Write a findings file noting: "No uncategorized operations found in trace"
  2. Return gracefully

If analysis script fails:

  1. Write a findings file with Status: ERROR
  2. CRITICAL: Do NOT manually analyze the raw CSV data
  3. CRITICAL: Do NOT provide any bottleneck findings

Read the full file on GitHub · 167 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 167 lines · 0 tokens per session scan A d13a912df7c8

Subscribe to this mod's changes

generic-op-analyzer is an agent published in the GitHub repository amd/skills (306 stars, last pushed 4d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,186 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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