starlark-dev
Skill558 starsChanged 3 years agoApache-2.0View on GitHub
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.
In this repository21 other files it gives its agents.
- cleanSkill
- cli-local-buildSkill
- cluster-manageSkill
- context-manageSkill
- docker-debugSkill
- docker-local-buildSkill
- dumpSkill
- enclave-inspectSkill
- engine-manageSkill
- files-inspectSkill
- gatewaySkill
- graflokiSkill
- import-composeSkill
- k8s-clean-clusterSkill
- k8s-debug-podsSkill
- k8s-dev-deploySkill
- lintSkill
- portalSkill
- port-forwardSkill
- run-packageSkill
- service-manageSkill
The file
We split this skill into the rules it gives an agent
2 rules. About 0 are common, 1 is distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 12
Create, debug, and test Kurtosis Starlark packages.
- Distinctive: line 158
Use a dry-run → execute → verify workflow:
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
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 pointkurtosis.yml
name: github.com/your-org/my-packagemain.star
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
# 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-runExecution model
Kurtosis Starlark executes in two phases:
- Planning phase — Your code runs and builds a plan of actions.
add_service(),exec(), etc. don't execute immediately — they return future references. - 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.
# 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
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
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
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
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
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:
# 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 -aCommon 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 |
Does it work?
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Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

