Code Review Checklist
shareAI-lab/learn-claude-code
Reviews code against a five-part checklist covering security, correctness, performance, maintainability and testing, and reports findings in a fixed format.
Intel VTune and AMD uProf profiling skill for microarchitecture analysis.
Install Intel Vtune Amd Uprof
$ npx skills add mohitmishra786/low-level-dev-skills --skill intel-vtune-amd-uprof -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install mohitmishra786/low-level-dev-skills intel-vtune-amd-uprof --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/mohitmishra786/low-level-dev-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/profilers/intel-vtune-amd-uprof .claude/skills/intel-vtune-amd-uprof && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "intel-vtune-amd-uprof" agent skill from https://github.com/mohitmishra786/low-level-dev-skills/tree/main/skills/profilers/intel-vtune-amd-uprof into .claude/skills/intel-vtune-amd-uprof/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "intel-vtune-amd-uprof", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/mohitmishra786/low-level-dev-skills/tree/main/skills/profilers/intel-vtune-amd-uprofType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add mohitmishra786/low-level-dev-skills --skill intel-vtune-amd-uprof -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install mohitmishra786/low-level-dev-skills intel-vtune-amd-uprof --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mohitmishra786/low-level-dev-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/profilers/intel-vtune-amd-uprof .agents/skills/intel-vtune-amd-uprof && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "intel-vtune-amd-uprof" agent skill from https://github.com/mohitmishra786/low-level-dev-skills/tree/main/skills/profilers/intel-vtune-amd-uprof into .agents/skills/intel-vtune-amd-uprof/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "intel-vtune-amd-uprof", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mohitmishra786/low-level-dev-skills --skill intel-vtune-amd-uprof -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install mohitmishra786/low-level-dev-skills intel-vtune-amd-uprof --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mohitmishra786/low-level-dev-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/profilers/intel-vtune-amd-uprof .cursor/skills/intel-vtune-amd-uprof && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "intel-vtune-amd-uprof" agent skill from https://github.com/mohitmishra786/low-level-dev-skills/tree/main/skills/profilers/intel-vtune-amd-uprof into .cursor/skills/intel-vtune-amd-uprof/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "intel-vtune-amd-uprof", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/mohitmishra786/low-level-dev-skills.git --path skills/profilers/intel-vtune-amd-uprof--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add mohitmishra786/low-level-dev-skills --skill intel-vtune-amd-uprof -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install mohitmishra786/low-level-dev-skills intel-vtune-amd-uprof --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mohitmishra786/low-level-dev-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/profilers/intel-vtune-amd-uprof .gemini/skills/intel-vtune-amd-uprof && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "intel-vtune-amd-uprof" agent skill from https://github.com/mohitmishra786/low-level-dev-skills/tree/main/skills/profilers/intel-vtune-amd-uprof into .gemini/skills/intel-vtune-amd-uprof/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "intel-vtune-amd-uprof", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install mohitmishra786/low-level-dev-skills intel-vtune-amd-uprofInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add mohitmishra786/low-level-dev-skills --skill intel-vtune-amd-uprof -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/mohitmishra786/low-level-dev-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/profilers/intel-vtune-amd-uprof .github/skills/intel-vtune-amd-uprof && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "intel-vtune-amd-uprof" agent skill from https://github.com/mohitmishra786/low-level-dev-skills/tree/main/skills/profilers/intel-vtune-amd-uprof into .github/skills/intel-vtune-amd-uprof/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "intel-vtune-amd-uprof", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mohitmishra786/low-level-dev-skills --skill intel-vtune-amd-uprof -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install mohitmishra786/low-level-dev-skills intel-vtune-amd-uprof --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mohitmishra786/low-level-dev-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/profilers/intel-vtune-amd-uprof .opencode/skills/intel-vtune-amd-uprof && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "intel-vtune-amd-uprof" agent skill from https://github.com/mohitmishra786/low-level-dev-skills/tree/main/skills/profilers/intel-vtune-amd-uprof into .opencode/skills/intel-vtune-amd-uprof/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "intel-vtune-amd-uprof", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
intel-vtune-amd-uprof- GitHub stars
- 252
- Token cost
- ~1.7k tokens
- SKILL.md length
- 357 words
- Files
- 1
- Skills in repo
- 138
- Repo updated
- First seen
- Licence
- MIT
At a glance
Intel VTune and AMD uProf profiling skill for microarchitecture analysis.
- Works in 7 steps: VTune setup (free Community Edition) → Analysis types → Hotspot analysis → …
- Analyzing hotspots
- SKILL.md covers Purpose, Triggers, Workflow and Related skills
- Reaches intel.com and amd.com
What it does
Intel Vtune Amd Uprof is an agent skill from mohitmishra786/low-level-dev-skills. Intel VTune and AMD uProf profiling skill for microarchitecture analysis. Use when analyzing hotspots, microarchitecture bottlenecks, memory access patterns, pipeline stalls, or using the roofline model. Covers VTune Community Edition (free) and AMD uProf as a free alternative. Activates on queries about VTune, uProf, microarchitecture analysis, pipeline stalls, memory bandwidth, roofline model, or hardware performance analysis.
Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Development, covering Performance optimization. The repository describes itself as: A curated suite of AI agent skills for systems and low-level programming with C/C++, Rust, and Zig toolchains, covering compilers, debuggers, profilers, build systems…. The licence is MIT.
When your agent uses it
- Analyzing hotspots
- Microarchitecture bottlenecks
- Memory access patterns
- Pipeline stalls
Example prompts
- “/intel-vtune-amd-uprof”
Workflow steps
7 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit bdc5847. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are bash).
From the folder's file list and the shell code blocks in SKILL.md.
Network
Hosts in commands or code, which the agent is likely to contact:
intel.comamd.com
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Intel Vtune Amd Uprof loads about 1.7k tokens when it runs. Until then it costs about 114 tokens; SKILL.md has 357 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from mohitmishra786/low-level-dev-skills at commit bdc5847, republished under its MIT licence (© mohitmishra786). 357 words, ~1,673 tokens.
Download SKILL.mdSave it as
.claude/skills/intel-vtune-amd-uprof/SKILL.md (or your agent's skills folder).- name
- intel-vtune-amd-uprof
- description
- Intel VTune and AMD uProf profiling skill for microarchitecture analysis. Use when analyzing hotspots, microarchitecture bottlenecks, memory access patterns, pipeline stalls, or using the roofline model. Covers VTune Community Edition (free) and AMD uProf as a free alternative. Activates on queries about VTune, uProf, microarchitecture analysis, pipeline stalls, memory bandwidth, roofline model, or hardware performance analysis.
Intel VTune & AMD uProf
Purpose
Guide agents through CPU microarchitecture profiling with Intel VTune Profiler (free Community Edition) and AMD uProf: hotspot identification, microarchitecture analysis, memory access pattern optimization, pipeline stall diagnosis, and roofline model analysis.
Triggers
- "How do I use Intel VTune to profile my code?"
- "What are pipeline stalls and how do I reduce them?"
- "How do I analyze memory bandwidth with VTune?"
- "What is the roofline model and how do I use it?"
- "How do I use AMD uProf as a free alternative to VTune?"
- "My code has good cache hit rates but is still slow"
Workflow
1. VTune setup (free Community Edition)
# Download Intel VTune Profiler (Community Edition — free)
# https://www.intel.com/content/www/us/en/developer/tools/oneapi/vtune-profiler.html
# Install on Linux
source /opt/intel/oneapi/vtune/latest/env/vars.sh
# CLI usage
vtune -collect hotspots ./prog
vtune -collect microarchitecture-exploration ./prog
vtune -collect memory-access ./prog
# View results in GUI
vtune-gui &
# File → Open Result → select .vtune directory
# Or use amplxe-cl (legacy CLI)
amplxe-cl -collect hotspots ./prog
amplxe-cl -report hotspots -r result/2. Analysis types
| Analysis | What it finds | When to use |
|---|---|---|
| Hotspots | CPU-bound functions | First step — find where time is spent |
| Microarchitecture Exploration | IPC, pipeline stalls, retired instructions | After hotspot — why is the hotspot slow? |
| Memory Access | Cache misses, DRAM bandwidth, NUMA | Memory-bound code |
| Threading | Lock contention, parallel efficiency | Multithreaded code |
| HPC Performance | Vectorization, memory, roofline | HPC / scientific code |
| I/O | Disk and network bottlenecks | I/O-bound code |
3. Hotspot analysis
# Collect and report hotspots
vtune -collect hotspots -result-dir hotspots_result ./prog
# Report top functions by CPU time
vtune -report hotspots -r hotspots_result -format csv | head -20
# CLI output example:
# Function CPU Time Module
# compute_fft 4.532s libfft.so
# matrix_mult 2.108s prog
# parse_input 0.234s progBuild with debug info for meaningful symbols:
gcc -O2 -g ./prog.c -o prog # symbols visible in VTune
gcc -O2 -g -gsplit-dwarf -fno-omit-frame-pointer ./prog.c -o prog # better stacksShow full SKILL.md (176 more words)Show less
4. Microarchitecture exploration — pipeline stalls
vtune -collect microarchitecture-exploration -r micro_result ./prog
vtune -report summary -r micro_resultKey metrics to examine:
| Metric | Meaning | Good value |
|---|---|---|
| IPC (Instructions Per Clock) | How many instructions retire per cycle | x86: aim for > 2.0 |
| CPI (Clocks Per Instruction) | Inverse of IPC | Lower is better |
| Bad Speculation | Branch mispredictions | < 5% |
| Front-End Bound | Instruction decode bottleneck | < 15% |
| Back-End Bound | Execution unit or memory stall | < 30% |
| Retiring | Useful work fraction | > 70% ideal |
| Memory Bound | % cycles waiting for memory | < 20% |
Pipeline Analysis (Top-Down Methodology):
├── Retiring (good, useful work)
├── Bad Speculation (branch mispredictions)
├── Front-End Bound
│ ├── Fetch Latency (I-cache misses, branch mispredicts)
│ └── Fetch Bandwidth
└── Back-End Bound
├── Memory Bound
│ ├── L1 Bound → L1 cache misses
│ ├── L2 Bound → L2 cache misses
│ ├── L3 Bound → L3 cache misses
│ └── DRAM Bound → main memory bandwidth limited
└── Core Bound → ALU/compute bound5. Memory access analysis
# Collect memory access profile
vtune -collect memory-access -r mem_result ./prog
# Key output sections:
# - Memory Bound: % time waiting for memory
# - LLC (Last Level Cache) Miss Rate
# - DRAM Bandwidth: GB/s achieved vs theoretical peak
# - NUMA: cross-socket accesses (for multi-socket systems)Reading DRAM bandwidth:
DRAM Bandwidth: 18.4 GB/s
Peak Theoretical: 51.2 GB/s
Utilization: 36% — likely not DRAM-boundIf DRAM-bound: optimize data layout (AoS → SoA), reduce working set, improve spatial locality.
6. AMD uProf — free alternative for AMD CPUs
# Download AMD uProf
# https://www.amd.com/en/developer/uprof.html
# CLI profiling
AMDuProfCLI collect --config tbp ./prog # time-based profiling
AMDuProfCLI collect --config assess ./prog # microarchitecture assessment
AMDuProfCLI collect --config memory ./prog # memory access
# Generate report
AMDuProfCLI report -i /tmp/uprof_result/ -o report.html
# Open GUI
AMDuProf &AMD uProf metrics map to VTune equivalents:
Retired Instructions→ IPC analysisBranch Mispredictions→ Bad SpeculationL1/L2/L3 Cache Misses→ Memory Bound levelsData Cache Accesses→ Cache efficiency
7. Roofline model
The roofline model shows whether code is compute-bound or memory-bound by comparing achieved performance against hardware limits:
Performance (GFLOPS/s)
| _______________
Peak | /
Perf | / compute bound
| /
| /
| / memory bandwidth bound
| /
+------------------------------→
Arithmetic Intensity (FLOPS/Byte)# VTune roofline collection
vtune -collect hpc-performance -r roofline_result ./prog
# Then: VTune GUI → Roofline view
# For manual calculation:
# Arithmetic Intensity = FLOPS / memory_bytes_accessed
# Peak FLOPS = CPUs × cores × freq × FLOPS_per_cycle_per_core
# Peak BW = from hardware spec (e.g., 51.2 GB/s for DDR4-3200 dual channel)
# likwid-perfctr for manual roofline data (Linux)
likwid-perfctr -C 0 -g FLOPS_DP ./prog # double-precision FLOPS
likwid-perfctr -C 0 -g MEM ./prog # memory bandwidthRelated skills
- Use
skills/profilers/hardware-countersfor raw PMU event collection with perf stat - Use
skills/profilers/linux-perffor perf-based profiling on Linux - Use
skills/low-level-programming/cpu-cache-optfor memory access pattern optimization - Use
skills/low-level-programming/simd-intrinsicsfor vectorization to increase FLOPS
© mohitmishra786, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in skills/profilers/intel-vtune-amd-uprof of mohitmishra786/low-level-dev-skills.
Open the folder on GitHubat commit bdc5847
Compare with similar skills
Intel Vtune Amd Uprof next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Intel Vtune Amd Uprof this skillmohitmishra786/low-level-dev-skills | 252 | — | ~1.7k | Automated safety check: Pass | MIT | |
| Code Review ChecklistshareAI-lab/learn-claude-code | 78k | 4 repos | ~1.1k | Automated safety check: Pass | MIT | |
| LLM Torch Profiler Analysissgl-project/sglang | 37k | 2 repos | ~6.4k | Automated safety check: Pass | Apache-2.0 | |
| Pycrazyguitar/pysheeet | 8.2k | — | ~886 | Automated safety check: Pass | MIT | |
| Cmux Debugging Guidemanaflow-ai/cmux | 28k | 1 repos | ~1.1k | Automated safety check: Pass | Custom licence | |
| Analyzing .NET Performancedotnet/skills | 5.6k | 3 repos | ~3.1k | Automated safety check: Pass | MIT |
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Related
Categories
Questions about Intel Vtune Amd Uprof
What does Intel Vtune Amd Uprof do?
Intel VTune and AMD uProf profiling skill for microarchitecture analysis. Intel Vtune Amd Uprof is an agent skill from mohitmishra786/low-level-dev-skills. Intel VTune and AMD uProf profiling skill for microarchitecture analysis.
When should I use Intel Vtune Amd Uprof?
Intel Vtune Amd Uprof fits situations like: analyzing hotspots; microarchitecture bottlenecks; memory access patterns; pipeline stalls.
How do I install Intel Vtune Amd Uprof in Claude Code?
Run `npx skills add mohitmishra786/low-level-dev-skills --skill intel-vtune-amd-uprof -a claude-code`. Or copy the skill folder (skills/profilers/intel-vtune-amd-uprof in mohitmishra786/low-level-dev-skills) into .claude/skills/intel-vtune-amd-uprof in your project. Claude Code loads it when a task matches its description.
How do I install Intel Vtune Amd Uprof in Codex?
Run `npx skills add mohitmishra786/low-level-dev-skills --skill intel-vtune-amd-uprof -a codex`. Or copy the skill folder (skills/profilers/intel-vtune-amd-uprof in mohitmishra786/low-level-dev-skills) into .agents/skills/intel-vtune-amd-uprof in your project. Codex loads it when a task matches its description.
Can I use Intel Vtune Amd Uprof in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mohitmishra786/low-level-dev-skills --skill intel-vtune-amd-uprof -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/intel-vtune-amd-uprof, .gemini/skills/intel-vtune-amd-uprof, .github/skills/intel-vtune-amd-uprof and .opencode/skills/intel-vtune-amd-uprof in your project.
What does Intel Vtune Amd Uprof need to run?
SKILL.md names no scripts, command-line tools or credentials: Intel Vtune Amd Uprof is instructions for the agent only.
Does Intel Vtune Amd Uprof access the network?
SKILL.md names 2 domains. In commands or code: intel.com and amd.com; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.
Is Intel Vtune Amd Uprof safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Intel Vtune Amd Uprof use?
Intel Vtune Amd Uprof is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Intel Vtune Amd Uprof use?
About 1.7k tokens (SKILL.md is roughly 6.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Intel Vtune Amd Uprof?
Skills that share tags, products or a category with Intel Vtune Amd Uprof: Code Review Checklist (shareAI-lab/learn-claude-code, 78k stars), LLM Torch Profiler Analysis (sgl-project/sglang, 37k stars), Py (crazyguitar/pysheeet, 8.2k stars) and Cmux Debugging Guide (manaflow-ai/cmux, 28k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Intel Vtune Amd Uprof?
mohitmishra786 (a GitHub user) maintains it in mohitmishra786/low-level-dev-skills, which has 252 GitHub stars. The repository holds 138 skills in this directory. The repository was last updated on June 27, 2026.
Source: mohitmishra786/low-level-dev-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.