deploy-chalk-function
How to deploy a chalk function ("chalkcompute.function"). Useful for deploying a stand-alone python function in Chalk's container infrastructure. Use when someone wants to run a python function remotely on Chalk, deploy a chalkcompute function, or asks about the chalkcompute SDK.
- Installs
- 918
- Last 24h
- +54
- Trending rank
- #3192
- Security
- Not audited
Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/chalk-ai/chalk-ai-plugins --skill deploy-chalk-function- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads deploy-chalk-function automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Deploy a Chalk function
Make a python file that uses the chalkcompute package (PyPI name is chalkcompute, not chalk-sandbox-sdk). Use a uv shebang. Pin Python to <3.14 because a transitive Rust dep (chalk-remote-call-python) builds against PyO3 which currently maxes out at 3.13.
#!/usr/bin/env -S uv run --script
#
# /// script
# requires-python = ">=3.12,<3.14"
# dependencies = ["chalkcompute"]
# ///
import chalkcompute
@chalkcompute.function()
def some_function(arg_1: str) -> str:
return f"hi {arg_1}"
if __name__ == "__main__":
print(some_function("world"))
Notes:
@chalkcompute.functionmust be called —@chalkcompute.function()(keyword-only args). Bare@chalkcompute.functionraisesTypeError: function() takes 0 positional arguments but 1 was given.- The decorator deploys the function at import time (builds image, uploads, registers).
- Calling the decorated function (
some_function("world")) invokes it remotely and returns the result.
Required env vars
The SDK reads creds from env, not from chalk CLI config. The env var is CHALK_ENVIRONMENT_ID, not CHALK_ENVIRONMENT.
CHALK_API_SERVER
CHALK_CLIENT_ID
CHALK_CLIENT_SECRET
CHALK_ENVIRONMENT_ID
You can read these out of chalk config output for the current project. Example invocation:
CHALK_API_SERVER=... CHALK_CLIENT_ID=... CHALK_CLIENT_SECRET=... CHALK_ENVIRONMENT_ID=... ./your_script.py
Without CHALK_ENVIRONMENT_ID you'll get a permission_denied error from CustomImageService.GetOrBuildCustomImage even though CHALK_CLIENT_ID/CHALK_CLIENT_SECRET are valid.
Local SDK source
If chalkcompute isn't on the configured index (e.g. the script can't resolve chalkcompute from PyPI), point uv at a local checkout of chalk-sandbox-sdk:
# [tool.uv.sources]
# chalkcompute = { path = "/path/to/chalk-sandbox-sdk" }
FAQ
What does the deploy-chalk-function skill do?
How to deploy a chalk function ("chalkcompute.function"). Useful for deploying a stand-alone python function in Chalk's container infrastructure. Use when someone wants to run a python function remotely on Chalk, deploy a chalkcompute function, or asks about the chalkcompute SDK.
How do I install deploy-chalk-function?
Run npx skills add https://github.com/chalk-ai/chalk-ai-plugins --skill deploy-chalk-function in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/deploy-chalk-function/ (personal) or .claude/skills/deploy-chalk-function/ (project).
Which AI agents can use deploy-chalk-function?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is deploy-chalk-function safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains deploy-chalk-function?
It is published by chalk-ai in chalk-ai/chalk-ai-plugins. It has 918 recorded installs.
More from chalk-ai/chalk-ai-plugins
accelerate-python-resolvers
chalk-ai/chalk-ai-plugins
Make Chalk Python resolvers statically accelerable. Use when the user asks to accelerate resolvers, fix static-acceleration diagnostics, check why a resolver "can't be accelerated", or speed up Python feature pipelines in a Chalk project (a repo with chalk.yaml/chalk.yml).
benchmark-vllm-model
chalk-ai/chalk-ai-plugins
Benchmark throughput and cost-per-token of a model served on vLLM in Chalk's container infrastructure. Use when someone asks for $/token, $/request, tokens/sec, "how much would it cost to self-host this model", GPU sizing for an LLM, or wants to compare a self-hosted model's economics against a hosted API.
debug-plan-cache-misses
chalk-ai/chalk-ai-plugins
Find and debug Chalk query plan cache misses from engine logs. Use when a query is replanning on every request, an "ad-hoc query request missed the plan cache" warning shows up, latency spikes from repeated planning, or someone asks why two seemingly identical queries don't share a cached plan. Drives the chalk logs CLI search.
chalk-hello
chalk-ai/chalk-ai-plugins
Print a friendly greeting from the Chalk plugin marketplace, used to verify plugin installation.
Popular devops & cloud skills
microsoft-foundry
microsoft/azure-skills
Build, deploy, evaluate, optimize, fine-tune, and manage Microsoft Foundry agents, models, and resources end to end. USE FOR: foundry, azd ai agent, azd provision/deploy, hosted agent scaffold/develop/run/deploy/troubleshoot, prompt agent create, managed harness agent create, GitHub Copilot harness agent, create agent, update agent, add tool to agent, invoke agent, agent insights, evaluate agent, batch eval, continuous eval, continuous monitoring, agent CI/CD, optimize prompt, improve prompt, optimize agent instructions, Agent Optimizer scaffold, dataset curation from traces, deploy model, model fine-tuning (SFT/DPO/RFT), Foundry project, RBAC, role assignment, permissions, quota, capacity, region, deployment failure, AI Services, create Foundry resource, knowledge index, customize deployment, onboard, availability, training-data, grader, distillation, large file upload. DO NOT USE FOR: Azure Functions, App Service, general Azure deploy (use azure-deploy), general Azure prep (use azure
azure-diagnostics
microsoft/azure-skills
Debug Azure production issues on Azure using AppLens, Azure Monitor, resource health, and safe triage. WHEN: debug production issues, troubleshoot app service, app service high CPU, app service deployment failure, troubleshoot container apps, container app 503 or target port mismatch, troubleshoot functions, function telemetry missing or stopped after a config/connection-string change, troubleshoot AKS, VM RDP, Linux SSH, VM black screen, can't connect to VM, reset VM password, NSG or firewall blocking, kubectl cannot connect, kube-system/CoreDNS failures, pod pending, crashloop, node not ready, upgrade failures, analyze logs, KQL, insights, image pull failures, cold start issues, health probe failures, resource health, root cause of errors, troubleshoot event hubs, troubleshoot service bus, messaging SDK error, AMQP connection failure, message lock lost, lock renewal during long-running processing, service bus dead letter.
azure-prepare
microsoft/azure-skills
Prepare azd-based Azure projects for deployment: generates azure.yaml, infrastructure (Bicep/Terraform), and Dockerfiles for the Azure Developer CLI (azd) workflow. USE ONLY when the user explicitly wants to use azd as the deployment tool, or the project already has an azure.yaml file. DO NOT USE FOR: non-azd deployments, Python App Service code-only deploys (use python-appservice-deploy), or cross-cloud migration (use azure-cloud-migrate). WHEN: prepare app for azd, create azure.yaml, set up azd infrastructure, modernize app for Azure with azd, deploy with azd, function app, timer trigger, service bus trigger, event-driven function, managed identity, generate Bicep, generate Terraform, create and deploy to Azure.
azure-ai
microsoft/azure-skills
Use for Azure AI: Search, Speech, OpenAI, Document Intelligence. Helps with search, vector/hybrid search, speech-to-text, text-to-speech, transcription, OCR. WHEN: AI Search, query search, vector search, hybrid search, semantic search, speech-to-text, text-to-speech, transcribe, OCR, convert text to speech.
azure-deploy
microsoft/azure-skills
Execute Azure deployments for ALREADY-PREPARED applications that have existing .azure/deployment-plan.md and infrastructure files. DO NOT use this skill when the user asks to CREATE a new application — use azure-prepare instead. This skill runs azd up, azd deploy, terraform apply, and az deployment commands with built-in error recovery. Requires .azure/deployment-plan.md from azure-prepare and validated status from azure-validate. WHEN: "run azd up", "run azd deploy", "execute deployment", "push to production", "push to cloud", "go live", "ship it", "bicep deploy", "terraform apply", "publish to Azure", "launch on Azure". DO NOT USE WHEN: "create and deploy", "build and deploy", "create a new app", "set up infrastructure", "create and deploy to Azure using Terraform" — use azure-prepare for these.
azure-validate
microsoft/azure-skills
Pre-deployment validation for Azure readiness. Run deep checks on configuration, infrastructure (Bicep or Terraform), RBAC role assignments, managed identity permissions, and prerequisites before deploying. WHEN: validate my app, check deployment readiness, run preflight checks, verify configuration, check if ready to deploy, validate azure.yaml, validate Bicep, test before deploying, troubleshoot deployment errors, validate Azure Functions, validate function app, validate serverless deployment, verify RBAC roles, check role assignments, review managed identity permissions, what-if analysis, validate Container Apps deployment.