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.
npx skills add AMD-AGI/Apex --skill rocprof-computegit clone --depth 1 https://github.com/AMD-AGI/ApexWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/amd-agi/apex/rocprof-compute)<a href="https://agentmods.dev/skills/amd-agi/apex/rocprof-compute"><img src="https://agentmods.dev/badge/skills/amd-agi/apex/rocprof-compute/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/amd-agi/apex/rocprof-compute"><img src="https://agentmods.dev/badge/skills/amd-agi/apex/rocprof-compute.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00037 | $0.00657 |
| Opus 5.5 | $0.00015 | $0.00263 |
| Sonnet 5.5 | $0.00007 | $0.00131 |
| Haiku 4.5 | $0.00004 | $0.00066 |
Grade A, and why
rocprof-compute 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 40 lines — stays where its author put it; the contents beside it link to each section on GitHub.
rocprof-compute Profiling
Purpose
- Capture AMD GPU kernel metrics, roofline data, and traces with rocprof-compute.
- Analyze collected workloads to identify bottlenecks (compute vs memory, cache/TCP/TCC/SQ utilization).
When to Use
- Need kernel-level performance diagnostics on AMD GPUs (MI200/MI300 family).
- Comparing different kernel implementations or launch configs.
- Triaging stalls/low occupancy indicated by runtime benchmarks.
How to Use
- Activate project venv and install rocprof-compute Python deps (once per environment):
source .venv/bin/activatepython -m pip install -r /opt/rocm-7.0.0/libexec/rocprofiler-compute/requirements.txt
- Profile a workload:
source .venv/bin/activate && rocprof-compute profile -n <name> --path <out_dir> --join-type kernel -b SQ -b TCP -b TCC -- <cmd> <args>- Example (paged attention ragged test):
rocprof-compute profile -n kernelgen --path rocprof_compute_profile --no-roof --join-type kernel -b SQ -b TCP -b TCC -- .venv/bin/python -O op_tests/test_pa_ragged.py -p Shomy -q none -c 128 - Prefer
--join-type kernelfor comparing same kernel across grids; switch togridif grid-sensitive. - Add/adjust
-bblocks to target specific hardware units; use--list-metrics <arch>if unsure. - Use
--no-roofto skip roofline if only counters are needed; remove it to gather roofline data.
- Analyze collected data:
rocprof-compute analyze --path <out_dir> -b <metric_ids>or--list-stats/--list-metrics <arch>to discover ids.- Example:
rocprof-compute analyze --path rocprof_compute_profile -b 2 - For interactive review, use
--gui(default port 8050 or--random-port) or--tui.
- Typical workflow checklist:
- Pick a short, reproducible workload and seed; pin
--name+--pathper experiment. - Collect counters (SQ/TCP/TCC) and optionally roofline in one run; avoid mixing many kernels in a single profile when isolating a hotspot.
- After analyze, inspect top stats, occupancy, LDS/HBM bandwidth, and hotspot kernels; rerun with filtered
--kernelor--dispatchif needed.
- Pick a short, reproducible workload and seed; pin
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 40 lines · 37 tokens per session scan A 77d545769ae0
rocprof-compute is a skill published in the GitHub repository AMD-AGI/Apex (78 stars, last pushed 23d ago), licensed MIT. It adds 37 tokens to every session and 657 once invoked, about $0.0001 per session on Opus 5.5. 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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