SGLang is a framework for running inference for large language models and multimodal models, meaning it processes inputs to produce model outputs such as text or other media. It is used to serve and accelerate open AI models and related workloads.
Borrowing it
Nothing to install: this file belongs to sgl-project/sglang. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/sgl-project/sglang/main/.claude/skills/sglang-bisect-ci-regression/SKILL.mdgit clone --depth 1 https://github.com/sgl-project/sglangWrote 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.
[](https://agentmods.dev/skills/sgl-project/sglang/sglang-bisect-ci-regression)<a href="https://agentmods.dev/skills/sgl-project/sglang/sglang-bisect-ci-regression"><img src="https://agentmods.dev/badge/skills/sgl-project/sglang/sglang-bisect-ci-regression/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.
<a href="https://agentmods.dev/skills/sgl-project/sglang/sglang-bisect-ci-regression"><img src="https://agentmods.dev/badge/skills/sgl-project/sglang/sglang-bisect-ci-regression.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk pass
- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00056 | $0.02548 |
| Opus 5 | $0.00028 | $0.01274 |
| Sonnet 5 | $0.00011 | $0.00510 |
| Haiku 4.5 | $0.00006 | $0.00255 |
Grade A, and why
sglang-bisect-ci-regression scanned grade A with 1 finding 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 11d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
ssh {SSH_TARGET} "docker exec {CONTAINER} bash -c 'cd /tmp && curl -L https://github.com/sgl-project/sglang/archive/refs/heads/main.tar.gz | tar xz && cd sglang-main && pip install -e \"python[all]\"'" How it starts
The opening of the file, as written. The whole thing — 225 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SGLang Bisect CI Regression
Investigate a consistently failing CI test to find the root cause - whether it's a code regression from a specific PR, a hardware/runner-specific issue, or an environment change. Optionally reproduce the failure on a remote GPU server.
Slash Command
/sglang-bisect-ci-regression <test_name_or_ci_url> [ssh_target] [docker_container]
When to Use This Skill
- A CI test is failing consistently on main (scheduled runs)
- You need to find which PR introduced a regression
- You suspect a runner-specific or GPU-specific issue
- You want to reproduce a CI failure on a remote server
Arguments
- First argument (required): Test file name (e.g.
test_lora_tp.py) or a GitHub Actions job URL - Second argument (optional): SSH target for remote reproduction (e.g.
user@host) - Third argument (optional): Docker container name on the SSH target (e.g.
sglang_dev)
If SSH target and docker container are not provided, the skill will only perform the CI log analysis and bisection, without remote reproduction. Ask the user for these if reproduction is needed and they weren't provided.
Background: Scheduled CI Runs
SGLang uses the pr-test.yml workflow with scheduled runs (cron-triggered) to periodically test the main branch. These runs are the primary data source for detecting regressions:
- Workflow:
pr-test.ymlwithevent: schedule - Branch:
main - Dashboard: https://github.com/sgl-project/sglang/actions/workflows/pr-test.yml?query=event%3Aschedule
- Frequency: Runs multiple times daily, each pinned to the HEAD of
mainat trigger time - Purpose: Catches regressions that slip through PR-level CI (e.g., interaction bugs between merged PRs, hardware-specific issues)
Always use these scheduled runs (not PR-triggered runs) when bisecting regressions on main. The --event schedule filter in gh run list ensures you only see these periodic main-branch runs.
Workflow
Phase 1: Extract the Failure Signature
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.
- 11d ago First seen · 225 lines · 56 tokens per session scan A 8807e22391ab
sglang-bisect-ci-regression is a skill published in the GitHub repository sgl-project/sglang (35,749 stars, last pushed yesterday), licensed Apache-2.0. It adds 56 tokens to every session and 2,548 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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