Vercel Composition Patterns
supabase/supabase
React composition patterns that scale. An agent skill from supabase/supabase.
Orchestrates continuous kernel optimization by chaining profiling, bottleneck diagnosis, tier-based optimization, verification, and benchmarking into an iterative loop.
Install Iterative Kernel Optimization Loop
$ npx skills add ZJLi2013/awesome-kernel-skills --skill iterative-kernel-optimization-loop -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install ZJLi2013/awesome-kernel-skills iterative-kernel-optimization-loop --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/ZJLi2013/awesome-kernel-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/system/optimize-loop .claude/skills/iterative-kernel-optimization-loop && 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 "iterative-kernel-optimization-loop" agent skill from https://github.com/ZJLi2013/awesome-kernel-skills/tree/main/skills/system/optimize-loop into .claude/skills/iterative-kernel-optimization-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "iterative-kernel-optimization-loop", 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/ZJLi2013/awesome-kernel-skills/tree/main/skills/system/optimize-loopType 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 ZJLi2013/awesome-kernel-skills --skill iterative-kernel-optimization-loop -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install ZJLi2013/awesome-kernel-skills iterative-kernel-optimization-loop --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ZJLi2013/awesome-kernel-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/system/optimize-loop .agents/skills/iterative-kernel-optimization-loop && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "iterative-kernel-optimization-loop" agent skill from https://github.com/ZJLi2013/awesome-kernel-skills/tree/main/skills/system/optimize-loop into .agents/skills/iterative-kernel-optimization-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "iterative-kernel-optimization-loop", 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 ZJLi2013/awesome-kernel-skills --skill iterative-kernel-optimization-loop -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install ZJLi2013/awesome-kernel-skills iterative-kernel-optimization-loop --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ZJLi2013/awesome-kernel-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/system/optimize-loop .cursor/skills/iterative-kernel-optimization-loop && 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 "iterative-kernel-optimization-loop" agent skill from https://github.com/ZJLi2013/awesome-kernel-skills/tree/main/skills/system/optimize-loop into .cursor/skills/iterative-kernel-optimization-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "iterative-kernel-optimization-loop", 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/ZJLi2013/awesome-kernel-skills.git --path skills/system/optimize-loop--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 ZJLi2013/awesome-kernel-skills --skill iterative-kernel-optimization-loop -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install ZJLi2013/awesome-kernel-skills iterative-kernel-optimization-loop --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ZJLi2013/awesome-kernel-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/system/optimize-loop .gemini/skills/iterative-kernel-optimization-loop && 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 "iterative-kernel-optimization-loop" agent skill from https://github.com/ZJLi2013/awesome-kernel-skills/tree/main/skills/system/optimize-loop into .gemini/skills/iterative-kernel-optimization-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "iterative-kernel-optimization-loop", 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 ZJLi2013/awesome-kernel-skills iterative-kernel-optimization-loopInstalls 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 ZJLi2013/awesome-kernel-skills --skill iterative-kernel-optimization-loop -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/ZJLi2013/awesome-kernel-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/system/optimize-loop .github/skills/iterative-kernel-optimization-loop && 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 "iterative-kernel-optimization-loop" agent skill from https://github.com/ZJLi2013/awesome-kernel-skills/tree/main/skills/system/optimize-loop into .github/skills/iterative-kernel-optimization-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "iterative-kernel-optimization-loop", 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 ZJLi2013/awesome-kernel-skills --skill iterative-kernel-optimization-loop -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install ZJLi2013/awesome-kernel-skills iterative-kernel-optimization-loop --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ZJLi2013/awesome-kernel-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/system/optimize-loop .opencode/skills/iterative-kernel-optimization-loop && 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 "iterative-kernel-optimization-loop" agent skill from https://github.com/ZJLi2013/awesome-kernel-skills/tree/main/skills/system/optimize-loop into .opencode/skills/iterative-kernel-optimization-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "iterative-kernel-optimization-loop", 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
iterative-kernel-optimization-loop- GitHub stars
- 102
- Token cost
- ~2.5k tokens
- SKILL.md length
- 593 words
- Files
- 1
- Skills in repo
- 12
- Repo updated
- First seen
- Licence
- None found
At a glance
Orchestrates continuous kernel optimization by chaining profiling, bottleneck diagnosis, tier-based optimization, verification, and benchmarking into an iterative loop.
- Works in 7 steps: Baseline → Profile → Diagnose → …
- You want to iteratively optimize a kernel until it meets a performance target
- SKILL.md covers Overview, The Loop, Configuration and Phase Details, plus 6 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Iterative Kernel Optimization Loop is an agent skill from ZJLi2013/awesome-kernel-skills. Orchestrates continuous kernel optimization by chaining profiling, bottleneck diagnosis, tier-based optimization, verification, and benchmarking into an iterative loop. This is the "main program" that drives the other skills. Use when you want to iteratively optimize a kernel until it meets a performance target, similar to AutoKernel.
Its SKILL.md is about 2.5k 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.
When your agent uses it
- You want to iteratively optimize a kernel until it meets a performance target
- Similar to AutoKernel
Example prompts
- “main program”
- “Use the iterative-kernel-optimization-loop skill to orchestrate continuous kernel optimization by chaining profiling, bottleneck diagnosis…”
- “/iterative-kernel-optimization-loop”
Requirements
- Python 3
Workflow steps
7 steps, taken from the step headings in SKILL.md.
- Baseline
- Profile
- Diagnose
- Optimize
- Verify
- Benchmark
- Decide
What it can do on your machine
Read from SKILL.md and the folder at commit aba7662. 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 markdown, yaml and python).
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
github.comarxiv.org
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
Iterative Kernel Optimization Loop loads about 2.5k tokens when it runs. Until then it costs about 93 tokens; SKILL.md has 593 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
Without a licence we can't republish the file, so here is its outline and opening line. It has 593 words (~2,468 tokens).
“This skill is the orchestration layer that chains the other skills into an automated, iterative optimization cycle. It turns awesome_kernel_skills from a static knowledge collection into an agent-driven optimization engine, similar to AutoKernel's program.md.”
- name
- iterative-kernel-optimization-loop
Files
Just SKILL.md in skills/system/optimize-loop of ZJLi2013/awesome-kernel-skills.
Open the folder on GitHubat commit aba7662
Compare with similar skills
Iterative Kernel Optimization Loop 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 |
|---|---|---|---|---|---|---|
| Iterative Kernel Optimization Loop this skillZJLi2013/awesome-kernel-skills | 102 | — | ~2.5k | Automated safety check: Pass | None | |
| Vercel Composition Patternssupabase/supabase | 111k | 59 repos | ~726 | Automated safety check: Pass | MIT | |
| Finishing a Development Branchobra/superpowers | 296k | 5 repos | ~1.9k | Automated safety check: Pass | MIT | |
| Typescript Advanced Typesrolling-scopes/rsschool-app | 10k | 25 repos | ~4.2k | Automated safety check: Pass | MPL-2.0 | |
| PR Babysitteropeninterpreter/openinterpreter | 69k | 3 repos | ~4.2k | Automated safety check: Pass | Apache-2.0 | |
| Code Review ChecklistshareAI-lab/learn-claude-code | 78k | 5 repos | ~1.1k | Automated safety check: Pass | MIT |
Similar skills
- Official
Finishing a Development Branch
obra/superpowers
Walks the last step of a branch: confirm tests pass, detect the git environment, ask how to integrate, carry out your choice and clean up the worktree.
Typescript Advanced Types
rolling-scopes/rsschool-app
Master TypeScript's advanced type system including generics, conditional types, mapped types, template literals, and utility types for building type-safe applications.
PR Babysitter
openinterpreter/openinterpreter
Watches an open GitHub pull request until it merges, handling review comments, diagnosing CI failures and retrying flaky checks along the way.
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.
Greploop
onyx-dot-app/onyx
Iteratively improves a PR (GitHub), MR (GitLab), or shelved changelist (Perforce) until Greptile gives it a 5/5 confidence score with zero unresolved comments.
More from ZJLi2013/awesome-kernel-skills
All 12 skills in this repoCross Entropy Kernel
ZJLi2013/awesome-kernel-skills
Optimize fused cross-entropy loss kernels in Triton for NVIDIA and AMD GPUs.
Flash Attention Kernel
ZJLi2013/awesome-kernel-skills
Optimize FlashAttention-style fused attention kernels in Triton for NVIDIA and AMD GPUs.
Fused Moe Kernel
ZJLi2013/awesome-kernel-skills
Optimize Fused Mixture-of-Experts (MoE) kernels in Triton for NVIDIA and AMD GPUs.
Gemm Kernel Optimization
ZJLi2013/awesome-kernel-skills
Optimize dense matrix multiplication (GEMM) kernels in Triton for NVIDIA and AMD GPUs.
Kernel Benchmark
ZJLi2013/awesome-kernel-skills
Unified kernel benchmarking protocol producing JSON results with latency, TFLOPS, GBps, and comparison against PyTorch baselines.
Kernel Profiling
ZJLi2013/awesome-kernel-skills
Profile GPU kernels using NCU (NVIDIA) or rocprof (AMD) to collect performance metrics.
Related
Categories
Questions about Iterative Kernel Optimization Loop
What does Iterative Kernel Optimization Loop do?
Orchestrates continuous kernel optimization by chaining profiling, bottleneck diagnosis, tier-based optimization, verification, and benchmarking into an iterative loop. Iterative Kernel Optimization Loop is an agent skill from ZJLi2013/awesome-kernel-skills. Orchestrates continuous kernel optimization by chaining profiling, bottleneck diagnosis, tier-based optimization, verification, and benchmarking into an iterative loop.
When should I use Iterative Kernel Optimization Loop?
Iterative Kernel Optimization Loop fits situations like: you want to iteratively optimize a kernel until it meets a performance target; similar to AutoKernel.
How do I install Iterative Kernel Optimization Loop in Claude Code?
Run `npx skills add ZJLi2013/awesome-kernel-skills --skill iterative-kernel-optimization-loop -a claude-code`. Or copy the skill folder (skills/system/optimize-loop in ZJLi2013/awesome-kernel-skills) into .claude/skills/iterative-kernel-optimization-loop in your project. Claude Code loads it when a task matches its description.
How do I install Iterative Kernel Optimization Loop in Codex?
Run `npx skills add ZJLi2013/awesome-kernel-skills --skill iterative-kernel-optimization-loop -a codex`. Or copy the skill folder (skills/system/optimize-loop in ZJLi2013/awesome-kernel-skills) into .agents/skills/iterative-kernel-optimization-loop in your project. Codex loads it when a task matches its description.
Can I use Iterative Kernel Optimization Loop 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 ZJLi2013/awesome-kernel-skills --skill iterative-kernel-optimization-loop -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/iterative-kernel-optimization-loop, .gemini/skills/iterative-kernel-optimization-loop, .github/skills/iterative-kernel-optimization-loop and .opencode/skills/iterative-kernel-optimization-loop in your project.
What does Iterative Kernel Optimization Loop need to run?
SKILL.md names no scripts, command-line tools or credentials: Iterative Kernel Optimization Loop is instructions for the agent only. Our summary lists: Python 3.
Does Iterative Kernel Optimization Loop access the network?
SKILL.md names 2 domains. As links in the text: github.com and arxiv.org. This is read from the text; nothing was executed.
Is Iterative Kernel Optimization Loop 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 Iterative Kernel Optimization Loop use?
No licence was found for Iterative Kernel Optimization Loop or its repository. Without one, default copyright applies: ask the author before reusing or redistributing it.
How many tokens does Iterative Kernel Optimization Loop use?
About 2.5k tokens (SKILL.md is roughly 9.9k 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 Iterative Kernel Optimization Loop?
Skills that share tags, products or a category with Iterative Kernel Optimization Loop: Vercel Composition Patterns (supabase/supabase, 111k stars), Finishing a Development Branch (obra/superpowers, 296k stars), Typescript Advanced Types (rolling-scopes/rsschool-app, 10k stars) and PR Babysitter (openinterpreter/openinterpreter, 69k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Iterative Kernel Optimization Loop?
ZJLi2013 (a GitHub user) maintains it in ZJLi2013/awesome-kernel-skills, which has 102 GitHub stars. The repository holds 12 skills in this directory. The repository was last updated on March 31, 2026.
Source: ZJLi2013/awesome-kernel-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.