research-deepspeed

Expert guidance for training machine-learning models across multiple computers or GPUs with DeepSpeed. DeepSpeed includes methods for reducing memory use and supporting mixed-precision, pipeline, and sparse training.

In plain words
What is it for?
Use it to plan ZeRO optimization, pipeline parallelism, FP16, BF16, FP8, 1-bit Adam, or sparse-attention training setups.
Why use it?
Distributed training can involve complex choices about memory, precision, and how work is split between devices.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/graycodeai/starling/research-deepspeed
Any agent
npx skills add GrayCodeAI/starling --skill research-deepspeed
Clone the repo
git clone --depth 1 https://github.com/GrayCodeAI/starling

Made for: Claude Code, Codex.

Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 293 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original 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 $0.00039 $0.00293
Opus 5 $0.00019 $0.00147
Sonnet 5 $0.00008 $0.00059
Haiku 4.5 $0.00004 $0.00029

Measured 2d ago against content hash c0f87fc123ac, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

research-deepspeed 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 2d 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.

categories/ai-ml/research-deepspeed/SKILL.md · 22 lines

What it actually says

Progressive disclosure index

The complete skill instructions are preserved in the ordered references below. Open the part whose headings match the current task; read all parts in order when the task spans sections or requires the complete procedure.

Detailed instructions

Files

What ships with it

2 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. 2d ago First seen · 22 lines · 39 tokens per session scan A c0f87fc123ac

Subscribe to this mod's changes

research-deepspeed is a skill published in the GitHub repository GrayCodeAI/starling (2 stars, last pushed 2d ago), licensed MIT. It adds 39 tokens to every session and 293 once invoked, about $0.0002 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 2026-08-31.

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