Agent skill

Kernel Correctness

by uw-syfi in uw-syfi/vibesys

Check a compute kernel against its task reference, including numerical tolerance, memory safety, and supported input variants.

MITAuto-check passed

Install Kernel Correctness

skills CLI
$ npx skills add uw-syfi/vibesys --skill kernel-correctness -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install uw-syfi/vibesys kernel-correctness --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/uw-syfi/vibesys.git skills-src && mkdir -p .claude/skills && cp -r skills-src/resources/skills/kernel-correctness .claude/skills/kernel-correctness && rm -rf skills-src

Use ~/.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/

Facts

Skill name
kernel-correctness
GitHub stars
103
Token cost
~309 tokens
SKILL.md length
135 words
Files
1
Skills in repo
18
Repo updated
First seen
Licence
MIT

At a glance

Check a compute kernel against its task reference, including numerical tolerance, memory safety, and supported input variants.

  • Kernel implementation
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Correctness failures

What it does

Kernel Correctness is an agent skill from uw-syfi/vibesys. Check a compute kernel against its task reference, including numerical tolerance, memory safety, and supported input variants. Use for kernel implementation or correctness failures.

Its SKILL.md is about 310 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: Can AI Agents Build Bespoke Systems? The licence is MIT.

When your agent uses it

  • Kernel implementation
  • Correctness failures

Example prompts

  • “/kernel-correctness”

What it can do on your machine

Read from SKILL.md and the folder at commit e78a078. 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

    No URLs in SKILL.md.

    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

Kernel Correctness loads about 309 tokens when it runs. Until then it costs about 50 tokens; SKILL.md has 135 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~50
When it runs · the whole SKILL.md, loaded when a task matches
~309

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 uw-syfi/vibesys at commit e78a078, republished under its MIT licence (© uw-syfi). 135 words, ~309 tokens.

Download SKILL.mdSave it as .claude/skills/kernel-correctness/SKILL.md (or your agent's skills folder).
name
kernel-correctness
description
Check a compute kernel against its task reference, including numerical tolerance, memory safety, and supported input variants. Use for kernel implementation or correctness failures.

Kernel correctness

Read the task's candidate contract and accuracy checker to identify the exact supported inputs and comparison rule. Translate the reference operation into invariants for every output element, including reductions, masks, aliasing, strides, and tails where applicable. Keep the evaluator-owned reference and checker unchanged.

When a case fails, isolate the smallest supported shape and input pattern that reproduces it. Compare intermediate values or one output tile against the reference, then distinguish indexing errors, missing synchronization, uninitialized memory, and allowed floating-point variation. Run the full checker after each fix; a passing benchmark shape is insufficient.

For parallel writes, establish which thread owns each address. For reductions, check accumulation dtype, order-sensitive tolerance, and behavior at zero or masked elements. If the contract requires repeatable output, verify repeated runs under the same input and reject race-dependent results.

© uw-syfi, 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 resources/skills/kernel-correctness of uw-syfi/vibesys.

Open the folder on GitHubat commit e78a078

Compare with similar skills

Kernel Correctness 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.

Kernel Correctness compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Kernel Correctness this skilluw-syfi/vibesys103—~309Automated safety check: PassMIT
Metal Kernelpytorch/pytorch104k—~4.9kAutomated safety check: PassCustom licence
Ito Computeaffaan-m/ECC274k1 repos~1.7kAutomated safety check: PassMIT
CorrectionNxcoreAI/EverRoom3k—~290Automated safety check: PassCustom licence
Add Jit Kernelsgl-project/sglang37k—~13kAutomated safety check: PassApache-2.0
Kernel Organizationsgl-project/sglang37k—~1.3kAutomated safety check: PassApache-2.0

Similar skills

  • Metal Kernel

    pytorch/pytorch

    Write Metal/MPS kernels for PyTorch operators. An agent skill from pytorch/pytorch.

    104k GitHub stars~4.9k tokensUpdated today
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  • Ito Compute

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  • Correction

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  • Add Jit Kernel

    sgl-project/sglang

    Step-by-step tutorial for adding a new lightweight JIT CUDA kernel to sglang.kernels JIT infrastructure and public operator groups

    37k GitHub stars~13k tokensUpdated today
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  • Kernel Organization

    sgl-project/sglang

    Apply the SGLang kernels RFC when adding, moving, splitting, or reviewing kernel APIs, registry metadata, kernel tests, benchmarks, and model-specific implementations.

    37k GitHub stars~1.3k tokensUpdated today
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  • Neuron Nki Writing

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  • Triage PRs

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Questions about Kernel Correctness

What does Kernel Correctness do?

Check a compute kernel against its task reference, including numerical tolerance, memory safety, and supported input variants. Kernel Correctness is an agent skill from uw-syfi/vibesys. Check a compute kernel against its task reference, including numerical tolerance, memory safety, and supported input variants.

When should I use Kernel Correctness?

Kernel Correctness fits situations like: kernel implementation; correctness failures.

How do I install Kernel Correctness in Claude Code?

Run `npx skills add uw-syfi/vibesys --skill kernel-correctness -a claude-code`. Or copy the skill folder (resources/skills/kernel-correctness in uw-syfi/vibesys) into .claude/skills/kernel-correctness in your project. Claude Code loads it when a task matches its description.

How do I install Kernel Correctness in Codex?

Run `npx skills add uw-syfi/vibesys --skill kernel-correctness -a codex`. Or copy the skill folder (resources/skills/kernel-correctness in uw-syfi/vibesys) into .agents/skills/kernel-correctness in your project. Codex loads it when a task matches its description.

Can I use Kernel Correctness 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 uw-syfi/vibesys --skill kernel-correctness -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/kernel-correctness, .gemini/skills/kernel-correctness, .github/skills/kernel-correctness and .opencode/skills/kernel-correctness in your project.

What does Kernel Correctness need to run?

SKILL.md names no scripts, command-line tools or credentials: Kernel Correctness is instructions for the agent only.

Does Kernel Correctness access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Kernel Correctness 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 Kernel Correctness use?

Kernel Correctness 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 Kernel Correctness use?

About 309 tokens (SKILL.md is roughly 1.2k 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 Kernel Correctness?

Skills that share tags, products or a category with Kernel Correctness: Metal Kernel (pytorch/pytorch, 104k stars), Ito Compute (affaan-m/ECC, 274k stars), Correction (NxcoreAI/EverRoom, 3k stars) and Add Jit Kernel (sgl-project/sglang, 37k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Kernel Correctness?

uw-syfi (a GitHub organization) maintains it in uw-syfi/vibesys, which has 103 GitHub stars. The repository holds 18 skills in this directory. The repository was last updated on October 6, 2026.

Source: uw-syfi/vibesys on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.