kai-scheduler/KAI-Scheduler is a Kubernetes scheduler that allocates GPU resources for AI and machine-learning workloads. It is used by Kubernetes cluster administrators to run interactive jobs, training, and inference while balancing resource use and fairness across teams, including in large GPU clusters. The catalogue add-ons provide instructions and skills for working with KAI Scheduler.
Borrowing it
Nothing to install: this file belongs to kai-scheduler/KAI-Scheduler. 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/kai-scheduler/KAI-Scheduler/main/AGENTS.mdgit clone --depth 1 https://github.com/kai-scheduler/KAI-SchedulerWrote 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/instructions/kai-scheduler/kai-scheduler/agents-md)<a href="https://agentmods.dev/instructions/kai-scheduler/kai-scheduler/agents-md"><img src="https://agentmods.dev/badge/instructions/kai-scheduler/kai-scheduler/agents-md.svg" alt="Measured on agentmods" height="20"></a>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 | $0.02107 | $0.02107 |
| Opus 5 | $0.01053 | $0.01053 |
| Sonnet 5 | $0.00421 | $0.00421 |
| Haiku 4.5 | $0.00211 | $0.00211 |
Grade A, and why
KAI-Scheduler AGENTS.md 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 7d 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.
How it starts
The opening of the file, as written. The whole thing — 203 lines — stays where its author put it; the contents beside it link to each section on GitHub.
KAI Scheduler - Agent Development Guide
KAI Scheduler is a Kubernetes scheduler optimized for GPU resource allocation in AI/ML workloads, built on kube-batch with a modular plugin architecture.
Build/Lint/Test Commands
Building
make build # Build all services (Docker-based)
make build-go SERVICE_NAME=scheduler # Build single service
Linting
make lint # Run all linters (fmt, vet, golangci-lint)
make fmt-go # Format Go code
make vet-go # Run go vet
Testing
unit and integration tests
- Test files MUST ALWAYS be in the same directory as code
- Test files names MUST ALWAYS end in
_test.go. Example:resolver_test.go
make test # Run all tests (unit + helm chart tests)
# Run a single test file
ginkgo -v ./pkg/scheduler/actions/allocate
# Run a specific test function
ginkgo -v --focus "TestHandleAllocation" ./pkg/scheduler/actions/allocate
# Run tests with Ginkgo (for integration tests)
ginkgo -v --focus "test name pattern" ./pkg/binder/controllers/integration_tests
# Run tests with envtest (requires setup-envtest)
make envtest
KUBEBUILDER_ASSETS="$(bin/setup-envtest use 1.34.0 -p path --bin-dir bin)" go test ./pkg/... -timeout 30m
E2E tests
E2E tests run against a real Kubernetes using kind cluster and are located in test/e2e/suites/.
# Run locally with Kind (recommended for development)
./hack/run-e2e-kind.sh # Full e2e suite
./hack/run-e2e-kind.sh --preserve-cluster # Keep cluster after tests
./hack/run-e2e-kind.sh --local-images-build # Build images locally
# Run specific test suites (requires cluster with KAI installed)
ginkgo -r --randomize-all ./test/e2e/suites/allocate
ginkgo -r --randomize-all --focus "quota" ./test/e2e/suites
# Run with verbose output and trace
ginkgo -r --randomize-all --trace -vv ./test/e2e/suites/preempt
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.
- 7d ago First seen · 203 lines · 2,107 tokens per session scan A 18340e7ce0d8
KAI-Scheduler AGENTS.md is an instructions file published in the GitHub repository kai-scheduler/KAI-Scheduler (1,492 stars, last pushed today), licensed Apache-2.0. It adds 2,107 tokens to every session, about $0.0105 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.
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