Agent skill

Validate Triton Ascend Accuracy

by Krusty84 in Krusty84/triton-ascend-agent-dev-kit

Validate Triton-Ascend kernel outputs against PyTorch references with dtype-aware tolerances, exact integer checks, bfloat16 promotion, and boolean handling.

Apache-2.0Auto-check passedAI & LLM Engineering

Install Validate Triton Ascend Accuracy

skills CLI

$ npx skills add Krusty84/triton-ascend-agent-dev-kit --skill validate-triton-ascend-accuracy -a claude-code

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

GitHub CLI

$ gh skill install Krusty84/triton-ascend-agent-dev-kit validate-triton-ascend-accuracy --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/Krusty84/triton-ascend-agent-dev-kit.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/validate-triton-ascend-accuracy .claude/skills/validate-triton-ascend-accuracy && 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/

Paste into Claude Code

Install the "validate-triton-ascend-accuracy" agent skill from https://github.com/Krusty84/triton-ascend-agent-dev-kit/tree/main/skills/validate-triton-ascend-accuracy into .claude/skills/validate-triton-ascend-accuracy/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "validate-triton-ascend-accuracy", 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

$skill-installer install https://github.com/Krusty84/triton-ascend-agent-dev-kit/tree/main/skills/validate-triton-ascend-accuracy

Type 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.

skills CLI

$ npx skills add Krusty84/triton-ascend-agent-dev-kit --skill validate-triton-ascend-accuracy -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install Krusty84/triton-ascend-agent-dev-kit validate-triton-ascend-accuracy --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/Krusty84/triton-ascend-agent-dev-kit.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/validate-triton-ascend-accuracy .agents/skills/validate-triton-ascend-accuracy && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "validate-triton-ascend-accuracy" agent skill from https://github.com/Krusty84/triton-ascend-agent-dev-kit/tree/main/skills/validate-triton-ascend-accuracy into .agents/skills/validate-triton-ascend-accuracy/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "validate-triton-ascend-accuracy", 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.

skills CLI

$ npx skills add Krusty84/triton-ascend-agent-dev-kit --skill validate-triton-ascend-accuracy -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install Krusty84/triton-ascend-agent-dev-kit validate-triton-ascend-accuracy --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/Krusty84/triton-ascend-agent-dev-kit.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/validate-triton-ascend-accuracy .cursor/skills/validate-triton-ascend-accuracy && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "validate-triton-ascend-accuracy" agent skill from https://github.com/Krusty84/triton-ascend-agent-dev-kit/tree/main/skills/validate-triton-ascend-accuracy into .cursor/skills/validate-triton-ascend-accuracy/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "validate-triton-ascend-accuracy", 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

$ gemini skills install https://github.com/Krusty84/triton-ascend-agent-dev-kit.git --path skills/validate-triton-ascend-accuracy

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add Krusty84/triton-ascend-agent-dev-kit --skill validate-triton-ascend-accuracy -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install Krusty84/triton-ascend-agent-dev-kit validate-triton-ascend-accuracy --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/Krusty84/triton-ascend-agent-dev-kit.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/validate-triton-ascend-accuracy .gemini/skills/validate-triton-ascend-accuracy && rm -rf skills-src

Use ~/.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/

Paste into Gemini CLI

Install the "validate-triton-ascend-accuracy" agent skill from https://github.com/Krusty84/triton-ascend-agent-dev-kit/tree/main/skills/validate-triton-ascend-accuracy into .gemini/skills/validate-triton-ascend-accuracy/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "validate-triton-ascend-accuracy", 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.

GitHub CLI

$ gh skill install Krusty84/triton-ascend-agent-dev-kit validate-triton-ascend-accuracy

Installs 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).

skills CLI

$ npx skills add Krusty84/triton-ascend-agent-dev-kit --skill validate-triton-ascend-accuracy -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/Krusty84/triton-ascend-agent-dev-kit.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/validate-triton-ascend-accuracy .github/skills/validate-triton-ascend-accuracy && rm -rf skills-src

Use ~/.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/

Paste into GitHub Copilot

Install the "validate-triton-ascend-accuracy" agent skill from https://github.com/Krusty84/triton-ascend-agent-dev-kit/tree/main/skills/validate-triton-ascend-accuracy into .github/skills/validate-triton-ascend-accuracy/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "validate-triton-ascend-accuracy", 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.

skills CLI

$ npx skills add Krusty84/triton-ascend-agent-dev-kit --skill validate-triton-ascend-accuracy -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install Krusty84/triton-ascend-agent-dev-kit validate-triton-ascend-accuracy --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/Krusty84/triton-ascend-agent-dev-kit.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/validate-triton-ascend-accuracy .opencode/skills/validate-triton-ascend-accuracy && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "validate-triton-ascend-accuracy" agent skill from https://github.com/Krusty84/triton-ascend-agent-dev-kit/tree/main/skills/validate-triton-ascend-accuracy into .opencode/skills/validate-triton-ascend-accuracy/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "validate-triton-ascend-accuracy", 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: validate-triton-ascend-accuracy
GitHub stars: 106
Token cost: ~649 tokens
SKILL.md length: 171 words
Files: 1
Skills in repo: 23
Repo updated: Aug 15, 2026
First seen: Oct 7, 2026
Licence: Apache-2.0

At a glance

Validate Triton-Ascend kernel outputs against PyTorch references with dtype-aware tolerances, exact integer checks, bfloat16 promotion, and boolean handling.

Works in 5 steps: Compute the PyTorch reference from the… → Assert identical output shape and dtype. → Compare floating-point tensors with… → …
An agent writes
SKILL.md covers Goal, Workflow, Implementation Pattern and Ascend Guardrails, plus 1 more section
Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Validate Triton Ascend Accuracy is an agent skill from Krusty84/triton-ascend-agent-dev-kit. Validate Triton-Ascend kernel outputs against PyTorch references with dtype-aware tolerances, exact integer checks, bfloat16 promotion, and boolean handling. Use when an agent writes or reviews NPU kernel tests, needs a reusable accuracy-comparison helper, or must choose an initial comparison policy for float16, bfloat16, float32, integer, or boolean outputs.

Its SKILL.md is about 650 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 AI & LLM Engineering, covering Deep learning. It works with PyTorch. The repository describes itself as: A toolkit for AI agents used for development on Triton-Ascend for Ascend NPU. The licence is Apache-2.0.

When your agent uses it

An agent writes
Reviews NPU kernel tests
Needs a reusable accuracy-comparison helper
Must choose an initial comparison policy for float16

Example prompts

“/validate-triton-ascend-accuracy”

Requirements

Python 3

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

Compute the PyTorch reference from the same inputs before interpreting performance.
Assert identical output shape and dtype.
Compare floating-point tensors with dtype-aware tolerances.
Compare integer and boolean tensors exactly.
Add edge shapes, tail masks, zeros, extreme values, and NaNs when the operator semantics allow them.

What it can do on your machine

Read from SKILL.md and the folder at commit 4ab5ee7. 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 python).
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

Validate Triton Ascend Accuracy loads about 649 tokens when it runs. Until then it costs about 98 tokens; SKILL.md has 171 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~98
When it runs · the whole SKILL.md, loaded when a task matches: ~649

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 Krusty84/triton-ascend-agent-dev-kit at commit 4ab5ee7, republished under its Apache-2.0 licence (© Krusty84). 171 words, ~649 tokens.

Download SKILL.mdSave it as .claude/skills/validate-triton-ascend-accuracy/SKILL.md (or your agent's skills folder).

name: validate-triton-ascend-accuracy
description: Validate Triton-Ascend kernel outputs against PyTorch references with dtype-aware tolerances, exact integer checks, bfloat16 promotion, and boolean handling. Use when an agent writes or reviews NPU kernel tests, needs a reusable accuracy-comparison helper, or must choose an initial comparison policy for float16, bfloat16, float32, integer, or boolean outputs.

Validate Triton-Ascend Accuracy

Goal

Make correctness checks explicit and consistent across Triton-Ascend kernel tests.

Workflow

Compute the PyTorch reference from the same inputs before interpreting performance.
Assert identical output shape and dtype.
Compare floating-point tensors with dtype-aware tolerances.
Compare integer and boolean tensors exactly.
Add edge shapes, tail masks, zeros, extreme values, and NaNs when the operator semantics allow them.

Implementation Pattern

python

def assert_ascend_close(actual, expected):
    assert actual.shape == expected.shape
    assert actual.dtype == expected.dtype
    dtype = actual.dtype

    if dtype == torch.float16:
        torch.testing.assert_close(
            actual, expected, rtol=1e-3, atol=1e-3, equal_nan=True
        )
    elif dtype == torch.bfloat16:
        torch.testing.assert_close(
            actual.float(), expected.float(),
            rtol=1e-3, atol=1e-3, equal_nan=True,
        )
    elif dtype == torch.float32:
        torch.testing.assert_close(
            actual, expected, rtol=1e-4, atol=1e-4, equal_nan=True
        )
    elif dtype in {torch.int8, torch.int16, torch.int32, torch.int64}:
        assert torch.equal(actual, expected)
    elif dtype == torch.bool:
        assert torch.equal(actual.cpu(), expected.cpu())
    else:
        raise ValueError(f"unsupported dtype: {dtype}")

Ascend Guardrails

Create inputs and run both implementations on the intended NPU device; avoid unnecessary transfers during comparison.
Promote bfloat16 only for the comparison, not for the kernel result.
Treat the listed tolerances as starting points, not universal guarantees. Tighten or relax them only from the operator's numerical analysis.
Use equal_nan=True only when matching NaN positions is acceptable for the operator.
Never let a permissive tolerance hide mismatched shapes, dtypes, infinities, or systematic bias.

Verification

Include a test that intentionally perturbs the result enough to fail, proving the chosen tolerance detects meaningful errors. For masked kernels, always include a shape that exercises the tail.

Files

Just SKILL.md in skills/validate-triton-ascend-accuracy of Krusty84/triton-ascend-agent-dev-kit.

Open the folder on GitHubat commit 4ab5ee7

Compare with similar skills

Validate Triton Ascend Accuracy 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.

Validate Triton Ascend Accuracy compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
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Add Uint Supportpytorch/pytorch	104k	2 repos	~2.3k	Automated safety check: Pass	Custom licence	today
CLIP Image-Text MatchingOrchestra-Research/AI-Research-SKILLs	13k	7 repos	~1.7k	Automated safety check: Pass	MIT	3 mo ago
Add Torch Shapes Examplefacebook/pyrefly	7.1k	—	~1.3k	Automated safety check: Pass	MIT	today
MUSA GPU Training Optimizeropen-infra-skills/infra-skills	141	—	~1.7k	Automated safety check: Pass	Apache-2.0	3 mo ago
Ghstack CIpytorch/pytorch	104k	—	~1.4k	Automated safety check: Pass	Custom licence	today

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Triton-Ascend Fused Attention
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Triton-Ascend Fused Softmax
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Works with

PyTorch

Questions about Validate Triton Ascend Accuracy

What does Validate Triton Ascend Accuracy do?

Validate Triton-Ascend kernel outputs against PyTorch references with dtype-aware tolerances, exact integer checks, bfloat16 promotion, and boolean handling. Validate Triton Ascend Accuracy is an agent skill from Krusty84/triton-ascend-agent-dev-kit. Validate Triton-Ascend kernel outputs against PyTorch references with dtype-aware tolerances, exact integer checks, bfloat16 promotion, and boolean handling.

When should I use Validate Triton Ascend Accuracy?

Validate Triton Ascend Accuracy fits situations like: an agent writes; reviews NPU kernel tests; needs a reusable accuracy-comparison helper; must choose an initial comparison policy for float16.

How do I install Validate Triton Ascend Accuracy in Claude Code?

Run `npx skills add Krusty84/triton-ascend-agent-dev-kit --skill validate-triton-ascend-accuracy -a claude-code`. Or copy the skill folder (skills/validate-triton-ascend-accuracy in Krusty84/triton-ascend-agent-dev-kit) into .claude/skills/validate-triton-ascend-accuracy in your project. Claude Code loads it when a task matches its description.

How do I install Validate Triton Ascend Accuracy in Codex?

Run `npx skills add Krusty84/triton-ascend-agent-dev-kit --skill validate-triton-ascend-accuracy -a codex`. Or copy the skill folder (skills/validate-triton-ascend-accuracy in Krusty84/triton-ascend-agent-dev-kit) into .agents/skills/validate-triton-ascend-accuracy in your project. Codex loads it when a task matches its description.

Can I use Validate Triton Ascend Accuracy 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 Krusty84/triton-ascend-agent-dev-kit --skill validate-triton-ascend-accuracy -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/validate-triton-ascend-accuracy, .gemini/skills/validate-triton-ascend-accuracy, .github/skills/validate-triton-ascend-accuracy and .opencode/skills/validate-triton-ascend-accuracy in your project.

What does Validate Triton Ascend Accuracy need to run?

SKILL.md names no scripts, command-line tools or credentials: Validate Triton Ascend Accuracy is instructions for the agent only. Our summary lists: Python 3.

Does Validate Triton Ascend Accuracy 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 Validate Triton Ascend Accuracy 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 Validate Triton Ascend Accuracy use?

Validate Triton Ascend Accuracy is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Validate Triton Ascend Accuracy use?

About 649 tokens (SKILL.md is roughly 2.6k 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 Validate Triton Ascend Accuracy?

Skills that share tags, products or a category with Validate Triton Ascend Accuracy: Add Uint Support (pytorch/pytorch, 104k stars), CLIP Image-Text Matching (Orchestra-Research/AI-Research-SKILLs, 13k stars), Add Torch Shapes Example (facebook/pyrefly, 7.1k stars) and MUSA GPU Training Optimizer (open-infra-skills/infra-skills, 141 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Validate Triton Ascend Accuracy?

Krusty84 (a GitHub user) maintains it in Krusty84/triton-ascend-agent-dev-kit, which has 106 GitHub stars. The repository holds 23 skills in this directory. The repository was last updated on August 15, 2026.

Source: Krusty84/triton-ascend-agent-dev-kit on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Validate Triton Ascend Accuracy

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Validate Triton-Ascend Accuracy

Goal

Workflow

Implementation Pattern

Ascend Guardrails

Verification

Files

Compare with similar skills

Similar skills

More from Krusty84/triton-ascend-agent-dev-kit

Related

Questions about Validate Triton Ascend Accuracy