Docstring
pytorch/pytorch
Write docstrings for PyTorch functions and methods following PyTorch conventions.
Run a bounded TileLang implementation and optimization task from a PyTorch reference or existing kernel through baseline analysis, a written plan, candidate edits, lowering inspection, validation…
Install Tilelang Optimization Loop
$ npx skills add sablin39/tilelang-cuda-skills --skill tilelang-optimization-loop -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install sablin39/tilelang-cuda-skills tilelang-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/sablin39/tilelang-cuda-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/tilelang-optimization-loop .claude/skills/tilelang-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 "tilelang-optimization-loop" agent skill from https://github.com/sablin39/tilelang-cuda-skills/tree/main/skills/tilelang-optimization-loop into .claude/skills/tilelang-optimization-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tilelang-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/sablin39/tilelang-cuda-skills/tree/main/skills/tilelang-optimization-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 sablin39/tilelang-cuda-skills --skill tilelang-optimization-loop -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install sablin39/tilelang-cuda-skills tilelang-optimization-loop --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/sablin39/tilelang-cuda-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/tilelang-optimization-loop .agents/skills/tilelang-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 "tilelang-optimization-loop" agent skill from https://github.com/sablin39/tilelang-cuda-skills/tree/main/skills/tilelang-optimization-loop into .agents/skills/tilelang-optimization-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tilelang-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 sablin39/tilelang-cuda-skills --skill tilelang-optimization-loop -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install sablin39/tilelang-cuda-skills tilelang-optimization-loop --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/sablin39/tilelang-cuda-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/tilelang-optimization-loop .cursor/skills/tilelang-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 "tilelang-optimization-loop" agent skill from https://github.com/sablin39/tilelang-cuda-skills/tree/main/skills/tilelang-optimization-loop into .cursor/skills/tilelang-optimization-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tilelang-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/sablin39/tilelang-cuda-skills.git --path skills/tilelang-optimization-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 sablin39/tilelang-cuda-skills --skill tilelang-optimization-loop -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install sablin39/tilelang-cuda-skills tilelang-optimization-loop --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/sablin39/tilelang-cuda-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/tilelang-optimization-loop .gemini/skills/tilelang-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 "tilelang-optimization-loop" agent skill from https://github.com/sablin39/tilelang-cuda-skills/tree/main/skills/tilelang-optimization-loop into .gemini/skills/tilelang-optimization-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tilelang-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 sablin39/tilelang-cuda-skills tilelang-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 sablin39/tilelang-cuda-skills --skill tilelang-optimization-loop -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/sablin39/tilelang-cuda-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/tilelang-optimization-loop .github/skills/tilelang-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 "tilelang-optimization-loop" agent skill from https://github.com/sablin39/tilelang-cuda-skills/tree/main/skills/tilelang-optimization-loop into .github/skills/tilelang-optimization-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tilelang-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 sablin39/tilelang-cuda-skills --skill tilelang-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 sablin39/tilelang-cuda-skills tilelang-optimization-loop --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/sablin39/tilelang-cuda-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/tilelang-optimization-loop .opencode/skills/tilelang-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 "tilelang-optimization-loop" agent skill from https://github.com/sablin39/tilelang-cuda-skills/tree/main/skills/tilelang-optimization-loop into .opencode/skills/tilelang-optimization-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tilelang-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
tilelang-optimization-loop- GitHub stars
- 145
- Token cost
- ~2.7k tokens
- SKILL.md length
- 1,310 words
- Files
- 7 (incl. references)
- Skills in repo
- 10
- Repo updated
- First seen
- Licence
- None found
At a glance
Run a bounded TileLang implementation and optimization task from a PyTorch reference or existing kernel through baseline analysis, a written plan, candidate edits, lowering inspection, validation…
- Works in 6 steps: Establish the contract and baseline → Write the draft, then an executable plan → Implement and inspect one candidate → …
- Iterative kernel work and reproducible handoffs
- SKILL.md covers 1. Establish the contract and…, 2. Write the draft, then an…, 3. Implement and inspect one… and 4. Validate, then measure, plus 2 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Tilelang Optimization Loop is an agent skill from sablin39/tilelang-cuda-skills. Run a bounded TileLang implementation and optimization task from a PyTorch reference or existing kernel through baseline analysis, a written plan, candidate edits, lowering inspection, validation, measurement, and promotion. Use for iterative kernel work and reproducible handoffs; use a specialist directly for a single API, debugging, or profiling question.
Its SKILL.md is about 2.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including reference files (for example `references/execution-harness.md`, `references/experiment-record.md` and `references/external-tools.md`).
It sits in AI & LLM Engineering, covering Deep learning. It works with PyTorch. The repository describes itself as: Skills for writing tilelang and debugging with CUDA toolkits.
When your agent uses it
- Iterative kernel work and reproducible handoffs
- Use a specialist directly for a single API
- Profiling question
Example prompts
- “/tilelang-optimization-loop”
Requirements
- Python 3
Workflow steps
6 steps, taken from the step headings in SKILL.md.
- Establish the contract and baseline
- Write the draft, then an executable plan
- Implement and inspect one candidate
- Validate, then measure
- Record a decision and choose the next experiment
- Reproduce and hand off
What it can do on your machine
Read from SKILL.md and the folder at commit 502a514. 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.
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.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
Tilelang Optimization Loop loads about 2.7k tokens when it runs, and up to ~9.7k if it reads all its reference files. Until then it costs about 97 tokens; SKILL.md has 1,310 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 1,310 words (~2,720 tokens).
“Follow a repeatable experiment cycle in the task workspace. Keep the skill suite and its upstream knowledge separate from generated kernels and results. Resume from evidence that still matches the source, inputs, and environment. This adapts the KDA workflow to…”
- name
- tilelang-optimization-loop
Files
SKILL.md and 6 other files (references) in skills/tilelang-optimization-loop of sablin39/tilelang-cuda-skills.
- SKILL.md
- references/execution-harness.md
- references/experiment-record.md
- references/external-tools.md
- references/joint-fwd-bwd.md
- references/kernelwiki.md
- references/worker-handoff.md
Open the folder on GitHubat commit 502a514
Compare with similar skills
Tilelang 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 |
|---|---|---|---|---|---|---|
| Tilelang Optimization Loop this skillsablin39/tilelang-cuda-skills | 145 | — | ~2.7k | Automated safety check: Pass | None | |
| Docstringpytorch/pytorch | 104k | 2 repos | ~2.6k | Automated safety check: Pass | Custom licence | |
| ExecuTorch Cortex-M Backendpytorch/executorch | 5.1k | — | ~872 | Automated safety check: Pass | Custom licence | |
| Qualcomm QNN Backend Developmentpytorch/executorch | 5.1k | — | ~1.8k | Automated safety check: Pass | Custom licence | |
| Pt2 Bug Basherpytorch/pytorch | 104k | — | ~3.5k | Automated safety check: Pass | Custom licence | |
| Formattingbrendanhasz/probflow | 175 | — | ~381 | Automated safety check: Pass | MIT |
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Debug PyTorch 2 compiler stack failures including Dynamo graph breaks, Inductor codegen errors, AOTAutograd crashes, and accuracy mismatches.
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Ensure consistent code formatting using the uv package manager and pre-commit.
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More from sablin39/tilelang-cuda-skills
All 10 skills in this repoTorch Profiling Tilelang Programs
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Inspect a PyTorch baseline with torch.compile graphs/code and torch.profiler before drafting a custom kernel, then compare TileLang and PyTorch timelines, forward/backward regions, and allocations.
Writing Tilelang Design Docs
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Write human-facing TileLang design documents for proposed or completed kernel implementations.
Cuda
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Draft, debug, and measure CUDA kernels and host launch workflows.
Debugging Tilelang Programs
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Diagnose TileLang compilation, host argument, memory-liveness, runtime, and numerical failures.
Designing With Tilefoundry
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Describe model or operator HIR with TileFoundry, inspect topology and placement, run static cost analysis, visualize authored dataflow, and check a runtime implementation against its evaluator.
Profiling Tilelang Programs
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Measure TileLang kernel and workflow performance, choose benchmark or timeline tools, and compare implementations fairly.
Related
Works with
Categories
Questions about Tilelang Optimization Loop
What does Tilelang Optimization Loop do?
Run a bounded TileLang implementation and optimization task from a PyTorch reference or existing kernel through baseline analysis, a written plan, candidate edits, lowering inspection, validation…. Tilelang Optimization Loop is an agent skill from sablin39/tilelang-cuda-skills. Run a bounded TileLang implementation and optimization task from a PyTorch reference or existing kernel through baseline analysis, a written plan, candidate edits, lowering inspection, validation, measurement, and promotion.
When should I use Tilelang Optimization Loop?
Tilelang Optimization Loop fits situations like: iterative kernel work and reproducible handoffs; use a specialist directly for a single API; profiling question.
How do I install Tilelang Optimization Loop in Claude Code?
Run `npx skills add sablin39/tilelang-cuda-skills --skill tilelang-optimization-loop -a claude-code`. Or copy the skill folder (skills/tilelang-optimization-loop in sablin39/tilelang-cuda-skills) into .claude/skills/tilelang-optimization-loop in your project. Claude Code loads it when a task matches its description.
How do I install Tilelang Optimization Loop in Codex?
Run `npx skills add sablin39/tilelang-cuda-skills --skill tilelang-optimization-loop -a codex`. Or copy the skill folder (skills/tilelang-optimization-loop in sablin39/tilelang-cuda-skills) into .agents/skills/tilelang-optimization-loop in your project. Codex loads it when a task matches its description.
Can I use Tilelang 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 sablin39/tilelang-cuda-skills --skill tilelang-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/tilelang-optimization-loop, .gemini/skills/tilelang-optimization-loop, .github/skills/tilelang-optimization-loop and .opencode/skills/tilelang-optimization-loop in your project.
What does Tilelang Optimization Loop need to run?
SKILL.md names no scripts, command-line tools or credentials: Tilelang Optimization Loop is instructions for the agent only. Our summary lists: Python 3.
Does Tilelang Optimization Loop access the network?
SKILL.md names 1 domain. As links in the text: github.com. This is read from the text; nothing was executed.
Is Tilelang 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 Tilelang Optimization Loop use?
No licence was found for Tilelang Optimization Loop or its repository. Without one, default copyright applies: ask the author before reusing or redistributing it.
How many tokens does Tilelang Optimization Loop use?
About 2.7k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 6.9k tokens, read only when the agent opens those files.
What are the alternatives to Tilelang Optimization Loop?
Skills that share tags, products or a category with Tilelang Optimization Loop: Docstring (pytorch/pytorch, 104k stars), ExecuTorch Cortex-M Backend (pytorch/executorch, 5.1k stars), Qualcomm QNN Backend Development (pytorch/executorch, 5.1k stars) and Pt2 Bug Basher (pytorch/pytorch, 104k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Tilelang Optimization Loop?
sablin39 (a GitHub user) maintains it in sablin39/tilelang-cuda-skills, which has 145 GitHub stars. The repository holds 10 skills in this directory. The repository was last updated on September 15, 2026.
Source: sablin39/tilelang-cuda-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.