sglang SKILL.md skillA
sglang from orchestra-research/ai-research-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add orchestra-research/ai-research-skills/sglang@v1.0.0Pins v1.0.0 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- orchestra-research/ai-research-skills
- Path
12-inference-serving/sglang/SKILL.md- Versions recorded
- 5
- Latest version
- v1.0.0, committed Nov 20, 2025
- First version recorded
- Nov 9, 2025
- Size
- 11,431 bytes
- Repository stars
- 13,718
- License
- MIT
Fast structured generation and serving for LLMs with RadixAttention prefix caching. Use for JSON/regex outputs, constrained decoding, agentic workflows with tool calls, or when you need 5× faster inference than vLLM with prefix sharing. Powers 300,000+ GPUs at xAI, AMD, NVIDIA, and LinkedIn.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# SGLang
High-performance serving framework for LLMs and VLMs with RadixAttention for automatic prefix caching.
## When to use SGLang
**Use SGLang when:**
- Need structured outputs (JSON, regex, grammar)
- Building agents with repeated prefixes (system prompts, tools)
- Agentic workflows with function calling
- Multi-turn conversations with shared context
- Need faster JSON decoding (3× vs standard)
**Use vLLM instead when:**
- Simple text generation without structure
- Don't need prefix caching
- Want mature, widely-tested production system
**Use TensorRT-LLM instead when:**
- Maximum single-request latency (no batching needed)
- NVIDIA-only deployment
- Need FP8/INT4 quantization on H100
## Quick start
### Installation
```bash
# pip install (recommended)
pip install "sglang[all]"
# With FlashInfer (faster, CUDA 11.8/12.1)
pip install sglang[all] flashinfer -i https://flashinfer.ai/whl/cu121/torch2.4/
# From source
git clone https://github.com/sgl-project/sglang.git
cd sglang
pip install -e "python[all]"
```
### Launch server
```bash
# Basic server (Llama 3-8B)
python -m sglang.launch_server \
--model-path meta-llama/Meta-Llama-3-8B-Instruct \
--port 30000
…Read the whole file at its exact version.
How to install
mdr add orchestra-research/ai-research-skills/sglang@sha256:05e664a43bb82df2The line at the top of this page pins the label v1.0.0, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_utjq3dt3iggmosdy)
1 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 5 versions of this file, between Nov 9, 2025 and Nov 20, 2025, about one every 3 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| v1.0.0 latest | 2025-11-20 | 0a9ded4 | 11,431 B | A | view · diff |
| v1.0.0 | 2025-11-20 | 51fc3a3 | 11,412 B | A | view · diff |
| v1.0.0 | 2025-11-20 | 81c38fe | 11,411 B | A | view · diff |
| v1.0.0 | 2025-11-19 | bd4461f | 11,410 B | A | view · diff |
| git:20251109.096b8f0 | 2025-11-09 | 096b8f0 | 11,166 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (11431 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
orchestra-research/ai-research-skills · 13,718 stars · license MIT · pushed 2026-10-11 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_utjq3dt3iggmosdy GET https://markdownregistry.com/api/v1/resolve?ref=orchestra-research/ai-research-skills/sglang GET https://markdownregistry.com/api/v1/blob/05e664a43bb82df2363ef22ceba81a41394a2b819c3367b2413f661485085c8f
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.