comanda
Generate, visualize, and execute declarative AI pipelines using the comanda.
Installation
npx clawhub@latest install comandaView the full skill documentation and source below.
Documentation
Comanda - Declarative AI Pipelines
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 <output.yaml> "<prompt>"
# 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 <workflow.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 <workflow.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