Step-by-step tutorial for adding a new lightweight JIT CUDA kernel to sglang.kernels JIT infrastructure and public operator groups
日本語の概要は準備中です。原文の説明を表示しています。
Start and persistently pursue a goal to babysit an SGLang pull request until selected GitHub Actions workflows pass on the latest PR head. Use when asked to monitor, babysit, retry, or fix PR CI for lint.yml, pr-test.yml, pr-test-extra.yml, AMD, or other named workflows; classify failures as PR-related versus flaky or infrastructural, auto-fix and push only small clean fixes, rerun failed jobs only up to 10 times, and ignore unselected workflows.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Drive only the selected workflows to green on the PR's latest head commit. Keep working across turns by starting a durable goal; do not stop merely because a run was dispatched, a retry began, or a fix was pushed.
Accept:
$babysit-pr-to-pass-ci [PR_NUMBER|PR_URL] [WORKFLOW ...]
$babysit-pr-to-pass-ci [PR_NUMBER|PR_URL] --only WORKFLOW [WORKFLOW ...]
lint.yml and pr-test.yml.--only, add named workflows to the two defaults.--only, monitor exactly the named workflows.pr-test-extra.yml, a repository path such as .github/workflows/pr-test-extra.yml, or an unambiguous workflow display name.extra as pr-test-extra.yml.Examples:
$babysit-pr-to-pass-ci
$babysit-pr-to-pass-ci 12345
$babysit-pr-to-pass-ci https://github.com/sgl-project/sglang/pull/12345 pr-test-extra.yml
$babysit-pr-to-pass-ci 12345 --only pr-test-amd.yml
Treat explicit invocation of this skill as authorization to create a goal and perform the scoped CI actions below.
Do not mark the goal complete until the completion check at the end of this skill succeeds.
.github/workflows/. Fail fast on ambiguous or nonexistent names.pr-test.yml.git status. Preserve all user changes. If a fix becomes necessary and the current checkout is dirty, on a different branch, or otherwise unsafe, use an isolated worktree for the PR head.Known SGLang gates:
pr-test.yml requires the run-ci label for relevant PR changes. If its existing gate job failed because the label was absent, add run-ci when authorized and rerun failed jobs in that existing run; adding the label alone does not necessarily create a new pr-test.yml run.pr-test-extra.yml requires both run-ci and run-ci-extra. It listens for relevant label events, so adding a missing label may create a fresh run. Prefer that fresh current-head run; rerun failed jobs in an existing current run only when needed.run-ci plus run-ci-extra gate. Verify the actual selected file.Adding the known CI opt-in labels is within scope. Do not add unrelated labels, mark the PR ready, alter reviewers, merge, or mutate other PR metadata.
Use both PR checks and workflow-run data so workflow names, run IDs, attempts, jobs, and logs can be correlated. Prefer workflow file IDs over display names when filtering runs.
For each selected workflow:
queued, requested, waiting, pending, and in_progress as active; keep monitoring.success.workflow_dispatch inputs or dispatch a workflow against the default branch when the intent is to test the PR head.After any user push or skill-authored push, re-read the PR head SHA, discard stale run selections, and start tracking the new head. Reset retry counters for the new head SHA.
Inspect the failed jobs and failed-step logs. In pr-test.yml, distinguish the root failure from cascade failures caused by check-pr-test-health, wait jobs, or final aggregation.
Record the exact failing test/check, error text, affected runner or hardware, and relevant log URL.
Compare the failure against the PR's changed files and diff.
Classify it:
PR-related when evidence ties the failure to changed code, tests, dependencies, configuration, generated files, or behavior introduced by the PR. A reproducible failure on the PR that does not occur on the base is strong evidence.
Unrelated/infrastructure when evidence points to a transient network or download error, runner loss, GPU/driver instability, service outage, pre-existing main-branch failure, known flaky threshold, unrelated test area, or another environmental cause.
Uncertain when evidence is insufficient. Do not label a failure flaky merely because it might be intermittent. Narrowly reproduce it, compare recent main/scheduled CI, inspect relevant code, or otherwise gather enough evidence to choose a category.
When several root failures exist, classify each one. Address PR-related failures before spending retries on unrelated cascades.
Estimate the proposed fix before editing.
A fix is eligible for automatic execution only when all are true:
If any condition fails, stop before editing. Report the diagnosis, proposed approach, expected files, estimated size, risks, and validation plan, then wait for user review.
For an eligible fix:
git add ., rewrite user commits, amend without request, or include pre-existing local changes.Retry only the failed jobs in the current selected-workflow run:
gh run rerun <RUN_ID> --failed --repo <OWNER/REPO>
Rules:
--failed.If GitHub cannot rerun only the failed portion of the selected run, stop and ask the user rather than rerunning the full workflow.
Before completing the goal:
success.Report the final PR URL, head SHA, selected workflows, passing run links, any commits pushed, and retry counts. Keep the report scoped to the selected workflows.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Step-by-step tutorial for adding a new lightweight JIT CUDA kernel to sglang.kernels JIT infrastructure and public operator groups
日本語の概要は準備中です。原文の説明を表示しています。
Step-by-step tutorial for adding a heavyweight AOT CUDA/C++ kernel to sgl-kernel (including tests & benchmarks)
日本語の概要は準備中です。原文の説明を表示しています。
Audit the existing test tree and CI configuration for improvements, using a catalog of patterns previously applied in this repo. Use when asked to audit tests or CI, shrink CI time or cost, find redundant or misplaced tests, clean up a test group, or review whether a CI change follows established practice.
日本語の概要は準備中です。原文の説明を表示しています。
Guide to SGLang CI workflow orchestration — stage ordering, fail-fast, gating, partitioning, execution modes, and debugging CI failures. Use when modifying CI workflows, adding stages, debugging CI pipeline issues, or understanding how tests are dispatched and gated across stages.
日本語の概要は準備中です。原文の説明を表示しています。
Audit SGLang startup logs, save evidence, and propose cleanup for user review. With no arguments, run Qwen3-8B at TP1 and TP2 plus gpt-oss-20b at TP1.
日本語の概要は準備中です。原文の説明を表示しています。
Compute the optimal --mamba-full-memory-ratio (or --max-mamba-cache-size pin) for a hybrid attention + linear-attention (Mamba / GDN / KDA) model's two serving memory pools, from the workload and serving config. Use when a user asks what ratio to set, why concurrency is clamped, or how to size the state vs KV pools for a hybrid model.
日本語の概要は準備中です。原文の説明を表示しています。