starlark-dev
Develop and debug Kurtosis Starlark packages. Create packages from scratch, understand the plan-based execution model, use print() debugging, handle future references, and test packages locally. Use when writing or troubleshooting .star files.
Best use case
starlark-dev is best used when you need a repeatable AI agent workflow instead of a one-off prompt. It is especially useful for teams working in multi. Develop and debug Kurtosis Starlark packages. Create packages from scratch, understand the plan-based execution model, use print() debugging, handle future references, and test packages locally. Use when writing or troubleshooting .star files.
Develop and debug Kurtosis Starlark packages. Create packages from scratch, understand the plan-based execution model, use print() debugging, handle future references, and test packages locally. Use when writing or troubleshooting .star files.
Users should expect a more consistent workflow output, faster repeated execution, and less time spent rewriting prompts from scratch.
Practical example
Example input
Use the "starlark-dev" skill to help with this workflow task. Context: Develop and debug Kurtosis Starlark packages. Create packages from scratch, understand the plan-based execution model, use print() debugging, handle future references, and test packages locally. Use when writing or troubleshooting .star files.
Example output
A structured workflow result with clearer steps, more consistent formatting, and an output that is easier to reuse in the next run.
When to use this skill
- Use this skill when you want a reusable workflow rather than writing the same prompt again and again.
When not to use this skill
- Do not use this when you only need a one-off answer and do not need a reusable workflow.
- Do not use it if you cannot install or maintain the related files, repository context, or supporting tools.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/starlark-dev/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How starlark-dev Compares
| Feature / Agent | starlark-dev | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Develop and debug Kurtosis Starlark packages. Create packages from scratch, understand the plan-based execution model, use print() debugging, handle future references, and test packages locally. Use when writing or troubleshooting .star files.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
AI Agents for Coding
Browse AI agent skills for coding, debugging, testing, refactoring, code review, and developer workflows across Claude, Cursor, and Codex.
Cursor vs Codex for AI Workflows
Compare Cursor and Codex for AI coding workflows, repository assistance, debugging, refactoring, and reusable developer skills.
SKILL.md Source
# Starlark Dev
Create, debug, and test Kurtosis Starlark packages.
## Package structure
A minimal Kurtosis package needs two files:
```
my-package/
kurtosis.yml # Package metadata
main.star # Entry point
```
### kurtosis.yml
```yaml
name: github.com/your-org/my-package
```
### main.star
```python
def run(plan, args):
plan.add_service(
name="my-service",
config=ServiceConfig(
image="nginx:latest",
ports={
"http": PortSpec(number=80, transport_protocol="TCP"),
},
),
)
```
## Running packages
```bash
# Run a local package
kurtosis run ./my-package
# Run with parameters
kurtosis run ./my-package '{"param1": "value1"}'
# Run a remote package from GitHub
kurtosis run github.com/ethpandaops/ethereum-package
# Run with a custom config file
kurtosis run github.com/ethpandaops/ethereum-package --args-file config.yaml
# Dry run (plan only, no execution)
kurtosis run ./my-package --dry-run
```
## Execution model
Kurtosis Starlark executes in two phases:
1. **Planning phase** — Your code runs and builds a plan of actions. `add_service()`, `exec()`, etc. don't execute immediately — they return future references.
2. **Execution phase** — The plan is executed in order. Future references are resolved to actual values.
This means you **cannot** use the return value of `plan.exec()` in Python-level logic like `if/else` during the planning phase. Use `plan.verify()` or `plan.assert()` instead.
```python
# WRONG: result is a future reference, not a real value during planning
result = plan.exec(service_name="my-service", recipe=ExecRecipe(command=["echo", "hello"]))
if result["output"] == "hello": # This won't work as expected
plan.print("matched")
# RIGHT: use plan.verify for conditional checks
result = plan.exec(service_name="my-service", recipe=ExecRecipe(command=["echo", "hello"]))
plan.verify(result["exit_code"], "==", 0)
```
## Debugging with print
```python
def run(plan, args):
plan.print("Args received: {}".format(args))
service = plan.add_service(
name="my-service",
config=ServiceConfig(image="nginx:latest"),
)
plan.print("Service IP: {}".format(service.ip_address))
plan.print("Service hostname: {}".format(service.hostname))
```
## Common patterns
### Wait for service readiness
```python
plan.wait(
service_name="my-service",
recipe=GetHttpRequestRecipe(port_id="http", endpoint="/health"),
field="code",
assertion="==",
target_value=200,
timeout="60s",
)
```
### Execute commands in a service
```python
result = plan.exec(
service_name="my-service",
recipe=ExecRecipe(command=["cat", "/etc/hostname"]),
)
plan.verify(result["exit_code"], "==", 0)
plan.print("Hostname: {}".format(result["output"]))
```
### Upload files
```python
config_template = read_file("./templates/config.toml")
artifact = plan.render_templates(
name="my-config",
config={
"config.toml": struct(
template=config_template,
data={"key": "value"},
),
},
)
plan.add_service(
name="my-service",
config=ServiceConfig(
image="my-image:latest",
files={"/etc/myapp": artifact},
),
)
```
### Import from other packages
```python
dependency = import_module("github.com/org/other-package/lib.star")
def run(plan, args):
dependency.some_function(plan)
```
## Testing
Use a dry-run → execute → verify workflow:
```bash
# 1. Validate the plan without executing
kurtosis run --dry-run ./my-package
# 2. Run and check output
kurtosis run ./my-package
# 3. Inspect the created enclave
kurtosis enclave inspect <enclave-name>
# 4. Check service logs
kurtosis service logs <enclave-name> <service-name>
# 5. Shell into a service to verify state
kurtosis service shell <enclave-name> <service-name>
# 6. Clean up after testing
kurtosis clean -a
```
## Common errors
| Error | Cause | Fix |
|-------|-------|-----|
| `cannot use future reference in if` | Using plan result in Python logic | Use `plan.verify()` or `plan.assert()` |
| `service not found` | Service name typo or not yet created | Check `plan.add_service()` name matches |
| `port not found` | Port ID mismatch | Ensure `port_id` in recipes matches `ports` dict key |
| `image pull failed` | Image doesn't exist or no auth | Verify image tag, check `docker pull` manually |
| `kurtosis.yml not found` | Running from wrong directory | Run from package root containing `kurtosis.yml` |Related Skills
service-manage
Manage services in Kurtosis enclaves. Add, inspect, stop, start, remove, update services. View logs, shell into containers, and execute commands. Use when you need to interact with running services.
run-package
Run Starlark scripts and packages with kurtosis run. Covers all flags including dry-run, args-file, parallel execution, image download modes, verbosity levels, and production mode. Use when executing Kurtosis packages locally or from GitHub.
portal
Manage Kurtosis Portal for remote context access. Start, stop, and check status of the Portal daemon that enables communication with remote Kurtosis servers. Use when working with remote Kurtosis contexts.
port-forward
View and manage port mappings for Kurtosis services. Check which local ports map to service ports and troubleshoot connectivity. Use when services aren't reachable or you need to find the right port.
lint
Lint and format Kurtosis Starlark files. Check syntax, validate docstrings, and auto-format .star files. Use when writing or reviewing Starlark packages to ensure code quality.
k8s-dev-deploy
Build, push, and deploy Kurtosis dev images to a Kubernetes cluster without creating a release. Rebuilds engine, core, and files-artifacts-expander as multi-arch Docker images with a unique tag, pushes to the logged-in user's Docker Hub, and restarts the engine. Use when testing local code changes on a k8s cluster.
k8s-debug-pods
Debug Kurtosis pods on Kubernetes. Diagnose why pods are Pending, CrashLoopBackOff, ImagePullBackOff, or Evicted. Check node taints, tolerations, resource pressure, and pod events. Use when kurtosis engine start fails or pods aren't coming online.
k8s-clean-cluster
Force-clean all Kurtosis resources from a Kubernetes cluster when kurtosis clean hangs or fails. Removes all kurtosis namespaces, pods, daemonsets, cluster roles, and cluster role bindings. Use when kurtosis clean -a hangs or leaves behind orphaned resources.
import-compose
Import Docker Compose files into Kurtosis. Convert docker-compose.yml to Starlark packages or run them directly. Use when migrating existing Docker Compose workflows to Kurtosis.
grafloki
Start Grafana and Loki for centralized log collection from Kurtosis enclaves. View aggregated service logs in a Grafana dashboard. Use when you need a UI for browsing logs across multiple services or want persistent log storage.
gateway
Start and manage the Kurtosis gateway for Kubernetes. The gateway forwards local ports to the Kurtosis engine and services running in a k8s cluster. Required when using Kurtosis with Kubernetes. Use when kurtosis engine status shows nothing on k8s or services aren't reachable.
files-inspect
Inspect, download, upload, and debug Kurtosis file artifacts. View artifacts in an enclave, download them locally for inspection, upload local files, and troubleshoot file mounting issues. Use when services can't find expected files or configs are wrong.