multiAI Summary Pending
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.
528 stars
Installation
Claude Code / Cursor / Codex
$curl -o ~/.claude/skills/starlark-dev/SKILL.md --create-dirs "https://raw.githubusercontent.com/kurtosis-tech/kurtosis/main/skills/starlark-dev/SKILL.md"
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 | multi | 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.
Which AI agents support this skill?
This skill is compatible with multi.
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.
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` |