一键导入
sparkgen-generate
Generate a new SparkGen-AWS project from the cookiecutter template
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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Generate a new SparkGen-AWS project from the cookiecutter template
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Develop and modify the SparkGen-AWS cookiecutter template — variables, hooks, files
Run cookiecutter matrix tests to verify template generates correctly across all variable combinations
Add, modify, remove, list, or show agents in the workflow
Send a chat message to the running agent server and display the response
Switch LLM providers, deployment modes, and manage environment configuration
Diagnose issues with Ollama, Docker, AWS, endpoints, guardrails, RAG, or general health
| name | sparkgen-generate |
| description | Generate a new SparkGen-AWS project from the cookiecutter template |
| user_invokable | true |
| auto_invokable | false |
| arguments | [project_name] [--mode local|docker|aws] [--agents 1-4] [--rag yes|no] [--provider bedrock|ollama|openai] |
Generate a new project from the SparkGen-AWS cookiecutter template.
Before generating:
cookiecutter.json to understand all available template variablescookiecutter --versionMap the user's arguments to cookiecutter variables:
| Argument | cookiecutter Variable | Default |
|---|---|---|
| project_name | project_name | "My SparkGen AWS Agent" |
| --mode | deployment_mode | "all" |
| --agents | num_agents | "4" |
| --rag | enable_rag | "yes" |
| --provider | llm_provider | "bedrock" |
Build the cookiecutter command with --no-input and variable overrides:
cookiecutter . --no-input \
project_name="<name>" \
deployment_mode="<mode>" \
num_agents="<N>" \
enable_rag="<yes|no>" \
llm_provider="<provider>"
After generating:
ls <output_slug>/python -m compileall <output_slug>/app -q<output_slug>/config/ai_workflow.yaml<output_slug>/Makefile<output_slug>/app/api.py<output_slug>/.claude/skills/ (skills directory)<output_slug>/CLAUDE.mdgrep "^ - name:" <output_slug>/config/ai_workflow.yaml=== Project Generated ===
Name: <project_name>
Location: ./<output_slug>/
Mode: <deployment_mode>
Provider: <llm_provider>
Agents: <num_agents>
RAG: <enable_rag>
Guardrails: <enable_guardrails>
Next steps:
cd <output_slug>
make setup # Install dependencies
make local # Start local dev server
Available skills (in generated project):
/sparkgen-deploy Deploy to local/docker/aws
/sparkgen-test Run tests
/sparkgen-chat Test chat
/sparkgen-debug Diagnose issues
pip install cookiecutter