Comanda
/install comanda
Comanda - Declarative AI Pipelines
🌐 Website: comanda.sh | 📦 GitHub: kris-hansen/comanda
Comanda defines LLM workflows in YAML and runs them from the command line. Workflows can chain multiple AI models, run steps in parallel, and pipe data through processing stages.
Installation
# macOS
brew install kris-hansen/comanda/comanda
# Or via Go
go install github.com/kris-hansen/comanda@latest
Then configure API keys:
comanda configure
Commands
Generate a Workflow
Create a workflow YAML from natural language:
comanda generate \x3Coutput.yaml> "\x3Cprompt>"
# Examples
comanda generate summarize.yaml "Create a workflow that summarizes text input"
comanda generate review.yaml "Analyze code for bugs, then suggest fixes" -m claude-sonnet-4-20250514
Visualize a Workflow
Display ASCII chart of workflow structure:
comanda chart \x3Cworkflow.yaml>
comanda chart workflow.yaml --verbose
Shows step relationships, models used, input/output chains, and validity.
Process/Execute a Workflow
Run a workflow file:
comanda process \x3Cworkflow.yaml>
# With input
cat file.txt | comanda process analyze.yaml
echo "Design a REST API" | comanda process multi-agent.yaml
# Multiple workflows
comanda process step1.yaml step2.yaml step3.yaml
View/Edit Workflows
Workflow files are YAML. Read them directly to understand or modify:
cat workflow.yaml
Workflow YAML Format
Basic Step
step_name:
input: STDIN | NA | filename | $VARIABLE
model: gpt-4o | claude-sonnet-4-20250514 | gemini-pro | ollama/llama2 | claude-code | gemini-cli
action: "Instruction for the model"
output: STDOUT | filename | $VARIABLE
Parallel Execution
parallel-process:
analysis-one:
input: STDIN
model: claude-sonnet-4-20250514
action: "Analyze for security issues"
output: $SECURITY
analysis-two:
input: STDIN
model: gpt-4o
action: "Analyze for performance"
output: $PERF
Chained Steps
extract:
input: document.pdf
model: gpt-4o
action: "Extract key points"
output: $POINTS
summarize:
input: $POINTS
model: claude-sonnet-4-20250514
action: "Create executive summary"
output: STDOUT
Generate + Process (Meta-workflows)
create_workflow:
input: NA
generate:
model: gpt-4o
action: "Create a workflow that analyzes sentiment"
output: generated.yaml
run_it:
input: NA
process:
workflow_file: generated.yaml
Available Models
Run comanda configure to set up API keys. Common models:
| Provider | Models |
|---|---|
| OpenAI | gpt-4o, gpt-4o-mini, o1, o1-mini |
| Anthropic | claude-sonnet-4-20250514, claude-opus-4-20250514 |
gemini-pro, gemini-flash |
|
| Ollama | ollama/llama2, ollama/mistral, etc. |
| Agentic | claude-code, gemini-cli, openai-codex |
Examples Location
See ~/clawd/comanda/examples/ for workflow samples:
agentic-loop/- Autonomous agent patternsclaude-code/- Claude Code integrationgemini-cli/- Gemini CLI workflowsdocument-processing/- PDF, text extractiondatabase-connections/- DB query workflows
Troubleshooting
- "model not configured": Run
comanda configureto add API keys - Workflow validation errors: Use
comanda chart workflow.yamlto visualize and check validity - Debug mode: Add
--debugflag for verbose logging
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install comanda - 安装完成后,直接呼叫该 Skill 的名称或使用
/comanda触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
Comanda 是什么?
Generate, visualize, and execute declarative AI pipelines using the comanda CLI. Use when creating LLM workflows from natural language, viewing workflow charts, editing YAML workflow files, or processing/running comanda workflows. Supports multi-model orchestration (OpenAI, Anthropic, Google, Ollama, Claude Code, Gemini CLI, Codex). 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 1982 次。
如何安装 Comanda?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install comanda」即可一键安装,无需额外配置。
Comanda 是免费的吗?
是的,Comanda 完全免费(开源免费),可自由下载、安装和使用。
Comanda 支持哪些平台?
Comanda 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 Comanda?
由 kris-hansen(@kris-hansen)开发并维护,当前版本 v1.0.2。