hipfire: Skill for Claude Code

.agents/skills/hipfire-kernel-tuning/SKILL.md

hipfire-kernel-tuning is a skill for Claude Code, Codex from warpfront/hipfire. It costs 126 tokens per session (1,718 once invoked), scanned A, original, no licence file.

A guide for improving hipfire’s GPU calculation kernels, the small programs that perform its computations. It covers choosing one performance change and checking both the generated instructions and fresh-run measurements.

In plain words
What is it for?
Use it after finding a slow kernel to test changes such as memory prefetching, tile sizes, wave size, GPU matrix instructions, fused calculations, or compiler instruction settings.
Why use it?
It helps verify that a speed improvement is real and does not cause problems in nearby code paths.

Skill for Claude CodeCodex

Which agent this was written for is unclear — body not stored (licence); the path alone says nothing. Also seen: installed under .agents/ (shared by several agents).

This is warpfront/hipfire's own configuration. It tells Claude Code and Codex how to work on hipfire itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything hipfire configures →

Reuse

Borrowing it

Nothing to install: this file belongs to warpfront/hipfire. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/warpfront/hipfire/master/.agents/skills/hipfire-kernel-tuning/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/warpfront/hipfire

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for hipfire-kernel-tuning

README.md
[![agentmods](https://agentmods.dev/badge/skills/warpfront/hipfire/hipfire-kernel-tuning/github.svg)](https://agentmods.dev/skills/warpfront/hipfire/hipfire-kernel-tuning)
Your own site
<a href="https://agentmods.dev/skills/warpfront/hipfire/hipfire-kernel-tuning"><img src="https://agentmods.dev/badge/skills/warpfront/hipfire/hipfire-kernel-tuning/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for hipfire-kernel-tuning

Your own site · 80×15
<a href="https://agentmods.dev/skills/warpfront/hipfire/hipfire-kernel-tuning"><img src="https://agentmods.dev/badge/skills/warpfront/hipfire/hipfire-kernel-tuning.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 126 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,718 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin unknown No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00126 $0.01718
Opus 5 $0.00063 $0.00859
Sonnet 5 $0.00025 $0.00344
Haiku 4.5 $0.00013 $0.00172

Measured 9d ago against content hash 4ee347f60ac1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

hipfire-kernel-tuning scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.agents/skills/hipfire-kernel-tuning/SKILL.md · 112 lines

The source is not reproduced here

A licence we could not identify

The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.

Read it on GitHub

Files

What ships with it

5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 112 lines · 126 tokens per session scan A 4ee347f60ac1

Subscribe to this mod's changes

hipfire-kernel-tuning is a skill published in the GitHub repository warpfront/hipfire (610 stars, last pushed yesterday), with no licence file. It adds 126 tokens to every session and 1,718 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

developing-with-streamlit

Use for ALL Streamlit tasks: creating, editing, debugging, beautifying, styling, theming, optimizing, or deploying Streamlit apps. Also custom components, st.components.v2, HTML/JS/CSS work. Discovers and loads version-matched reference docs from the user's installed Streamlit (>=1.57). Triggers: streamlit, st.…

streamlit/streamlit · 128 tokens

trulens-instrumentation

Instrument LLM apps with TruLens OTEL-based tracing - from setup to debugging and optimization.

truera/trulens · 25 tokens

trulens-diagnosis

Diagnose low evaluation scores and generate actionable improvement recommendations.

truera/trulens · 17 tokens

neuron-debugger

Debug and monitor Neuron AI applications with Inspector APM, event observability, logging, and performance analysis. Use this skill whenever the user mentions debugging, monitoring, observability, performance analysis, tracing, Inspector, or needs to understand why an agent is behaving a certain way. Also trigger for…

neuron-core/neuron-ai · 90 tokens

plano-observability-debugging

Improve Plano tracing and debugging workflows. Use for sampling strategy, span attributes, and trace query-based root-cause analysis.

katanemo/plano · 32 tokens

wax-performance-audit

Benchmarking and performance auditing for the Wax repo. Use when running or interpreting Wax benchmarks, diagnosing CPU, memory, or I/O bottlenecks, or investigating Swift 6.2 concurrency issues such as Sendable, actor isolation, @unchecked Sendable, task-group fan-out, and data races.

christopherkarani/Wax · 67 tokens