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Agent skill

Fuse Triton Ascend Cat Conv1d

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

Refactor fused causal Conv1d state updates for Triton-Ascend by replacing negative-offset cat emulation and tl.where selection with transposed UB assembly through extension.insertslice.

Apache-2.0Auto-check passedAI & LLM Engineering

Install Fuse Triton Ascend Cat Conv1d

skills CLI
$ npx skills add Krusty84/triton-ascend-agent-dev-kit --skill fuse-triton-ascend-cat-conv1d -a claude-code

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

GitHub CLI
$ gh skill install Krusty84/triton-ascend-agent-dev-kit fuse-triton-ascend-cat-conv1d --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/fuse-triton-ascend-cat-conv1d .claude/skills/fuse-triton-ascend-cat-conv1d && 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
fuse-triton-ascend-cat-conv1d
GitHub stars
106
Token cost
~646 tokens
SKILL.md length
235 words
Files
1
Skills in repo
23
Repo updated
First seen
Licence
Apache-2.0

At a glance

Refactor fused causal Conv1d state updates for Triton-Ascend by replacing negative-offset cat emulation and tl.where selection with transposed UB assembly through extension.insertslice.

  • Works in 6 steps: Preserve the reference contract for x,… → Load state and input from nonnegative… → Transpose or reshape them so… → …
  • An agent ports causalconv1dupdate-style kernels
  • 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

Fuse Triton Ascend Cat Conv1d is an agent skill from Krusty84/triton-ascend-agent-dev-kit. Refactor fused causal Conv1d state updates for Triton-Ascend by replacing negative-offset cat emulation and tl.where selection with transposed UB assembly through extension.insertslice. Use when an agent ports causalconv1dupdate-style kernels, sees discrete scalar loads from negative offsets, suffers 32-byte tail-axis padding, or launches far more logical tasks than Ascend vector cores.

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. 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 ports causalconv1dupdate-style kernels
  • Sees discrete scalar loads from negative offsets
  • Suffers 32-byte tail-axis padding
  • Launches far more logical tasks than Ascend vector cores

Example prompts

  • “/fuse-triton-ascend-cat-conv1d”

Requirements

  • Python 3

Workflow steps

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

  1. Preserve the reference contract for x, conv_state, depthwise weights, bias, activation, and state-row indices.
  2. Load state and input from nonnegative contiguous addresses.
  3. Transpose or reshape them so concatenation occurs along a contiguous flattened UB axis.
  4. Insert state followed by new tokens with extension.insert_slice.
  5. Derive the new state tail and convolution windows from the assembled tensor.
  6. Map work to approximately the available vector-core count and loop over remaining feature tiles inside each program.

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

Fuse Triton Ascend Cat Conv1d loads about 646 tokens when it runs. Until then it costs about 106 tokens; SKILL.md has 235 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~106
When it runs · the whole SKILL.md, loaded when a task matches
~646

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). 235 words, ~646 tokens.

Download SKILL.mdSave it as .claude/skills/fuse-triton-ascend-cat-conv1d/SKILL.md (or your agent's skills folder).
name
fuse-triton-ascend-cat-conv1d
description
Refactor fused causal Conv1d state updates for Triton-Ascend by replacing negative-offset cat emulation and tl.where selection with transposed UB assembly through extension.insert_slice. Use when an agent ports causal_conv1d_update-style kernels, sees discrete scalar loads from negative offsets, suffers 32-byte tail-axis padding, or launches far more logical tasks than Ascend vector cores.

Fuse Triton-Ascend Cat and Causal Conv1d

Goal

Join convolution state and new tokens in UB, update the cached tail, and compute grouped causal Conv1d without materializing a global concatenation.

Workflow

  1. Preserve the reference contract for x, conv_state, depthwise weights, bias, activation, and state-row indices.
  2. Load state and input from nonnegative contiguous addresses.
  3. Transpose or reshape them so concatenation occurs along a contiguous flattened UB axis.
  4. Insert state followed by new tokens with extension.insert_slice.
  5. Derive the new state tail and convolution windows from the assembled tensor.
  6. Map work to approximately the available vector-core count and loop over remaining feature tiles inside each program.

Implementation Pattern

python
import triton.language.extra.cann.extension as extension

state_t = load_state_as_contiguous_transposed_tile()
x_t = load_input_as_contiguous_transposed_tile()
joined = tl.zeros((CAT_LEN * DIM_BLOCK,), dtype=x_ptr.dtype.element_ty)
joined = extension.insert_slice(
    joined, state_t, (0,), (STATE_LEN * DIM_BLOCK,), (1,)
)
joined = extension.insert_slice(
    joined, x_t, (STATE_LEN * DIM_BLOCK,), (SEQ_LEN * DIM_BLOCK,), (1,)
)

Ascend Guardrails

  • Do not emulate cat with negative pointer offsets plus tl.where; Triton-Ascend may classify it as discrete scalar access.
  • Use extension.insert_slice, not deprecated tl.insert_slice.
  • Account for Ascend UB padding of the final axis to 32 bytes.
  • For short final axes such as 1 or 3, consider a proven reshape-transpose “borrowed axis” layout only when total storage alignment permits it.
  • Include transpose cost and padding in the UB budget.
  • Query the target vector-core count instead of hardcoding a 40/48-core assumption.
  • Verify state updates when state indices repeat; concurrent writes need an explicit ordering policy.

Verification

Compare output and updated conv_state with the PyTorch reference for activation=None and SiLU, several state/sequence lengths, repeated and unique state indices, short widths, and feature dimensions that trigger alignment padding.

© Krusty84, Apache-2.0. 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/fuse-triton-ascend-cat-conv1d of Krusty84/triton-ascend-agent-dev-kit.

Open the folder on GitHubat commit 4ab5ee7

Compare with similar skills

Fuse Triton Ascend Cat Conv1d 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.

Fuse Triton Ascend Cat Conv1d compared with similar skills
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Add Uint Supportpytorch/pytorch104k2 repos~2.3kAutomated safety check: PassCustom licence
LLM Benchmarking with lm-evaluation-harnessOrchestra-Research/AI-Research-SKILLs13k8 repos~3kAutomated safety check: PassMIT
Segment Anything Model GuideOrchestra-Research/AI-Research-SKILLs13k8 repos~3.3kAutomated safety check: PassMIT
1passwordtrpc-group/trpc-agent-go1.9k14 repos~656Automated safety check: PassApache-2.0

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Categories

Questions about Fuse Triton Ascend Cat Conv1d

What does Fuse Triton Ascend Cat Conv1d do?

Refactor fused causal Conv1d state updates for Triton-Ascend by replacing negative-offset cat emulation and tl.where selection with transposed UB assembly through extension.insertslice. Fuse Triton Ascend Cat Conv1d is an agent skill from Krusty84/triton-ascend-agent-dev-kit.insertslice.

When should I use Fuse Triton Ascend Cat Conv1d?

Fuse Triton Ascend Cat Conv1d fits situations like: an agent ports causalconv1dupdate-style kernels; sees discrete scalar loads from negative offsets; suffers 32-byte tail-axis padding; launches far more logical tasks than Ascend vector cores.

How do I install Fuse Triton Ascend Cat Conv1d in Claude Code?

Run `npx skills add Krusty84/triton-ascend-agent-dev-kit --skill fuse-triton-ascend-cat-conv1d -a claude-code`. Or copy the skill folder (skills/fuse-triton-ascend-cat-conv1d in Krusty84/triton-ascend-agent-dev-kit) into .claude/skills/fuse-triton-ascend-cat-conv1d in your project. Claude Code loads it when a task matches its description.

How do I install Fuse Triton Ascend Cat Conv1d in Codex?

Run `npx skills add Krusty84/triton-ascend-agent-dev-kit --skill fuse-triton-ascend-cat-conv1d -a codex`. Or copy the skill folder (skills/fuse-triton-ascend-cat-conv1d in Krusty84/triton-ascend-agent-dev-kit) into .agents/skills/fuse-triton-ascend-cat-conv1d in your project. Codex loads it when a task matches its description.

Can I use Fuse Triton Ascend Cat Conv1d 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 fuse-triton-ascend-cat-conv1d -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/fuse-triton-ascend-cat-conv1d, .gemini/skills/fuse-triton-ascend-cat-conv1d, .github/skills/fuse-triton-ascend-cat-conv1d and .opencode/skills/fuse-triton-ascend-cat-conv1d in your project.

What does Fuse Triton Ascend Cat Conv1d need to run?

SKILL.md names no scripts, command-line tools or credentials: Fuse Triton Ascend Cat Conv1d is instructions for the agent only. Our summary lists: Python 3.

Does Fuse Triton Ascend Cat Conv1d 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 Fuse Triton Ascend Cat Conv1d 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 Fuse Triton Ascend Cat Conv1d use?

Fuse Triton Ascend Cat Conv1d 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 Fuse Triton Ascend Cat Conv1d use?

About 646 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 Fuse Triton Ascend Cat Conv1d?

Skills that share tags, products or a category with Fuse Triton Ascend Cat Conv1d: Agent Builder (shareAI-lab/learn-claude-code, 78k stars), Add Uint Support (pytorch/pytorch, 104k stars), LLM Benchmarking with lm-evaluation-harness (Orchestra-Research/AI-Research-SKILLs, 13k stars) and Segment Anything Model Guide (Orchestra-Research/AI-Research-SKILLs, 13k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Fuse Triton Ascend Cat Conv1d?

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.