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kris-hansen

Comanda

by kris-hansen · GitHub ↗ · v1.0.2
cross-platform ⚠ suspicious
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Install in OpenClaw
/install comanda
Description
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).
README (SKILL.md)

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
Google 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 patterns
  • claude-code/ - Claude Code integration
  • gemini-cli/ - Gemini CLI workflows
  • document-processing/ - PDF, text extraction
  • database-connections/ - DB query workflows

Troubleshooting

  • "model not configured": Run comanda configure to add API keys
  • Workflow validation errors: Use comanda chart workflow.yaml to visualize and check validity
  • Debug mode: Add --debug flag for verbose logging
Usage Guidance
This skill is an instruction-only integration for the comanda CLI and is coherent with that purpose. Before using it: (1) Only install the actual comanda binary from trusted sources (brew or the official repo); verify the GitHub repo and release signatures if possible. (2) Inspect any workflow YAML before running it — workflows can read files, environment variables, fetch URLs, and invoke agentic models that may run shell commands. Do not run untrusted workflows on sensitive hosts or with credentials in your environment. (3) When configuring provider API keys, follow least-privilege practices and prefer separate keys/accounts for automation. (4) If you want the skill to run autonomously, be extra cautious because workflows could be crafted to access local secrets or exfiltrate data. If you need, ask the publisher for provenance (official homepage/repo tags) to increase confidence.
Capability Analysis
Type: OpenClaw Skill Name: comanda Version: 1.0.2 The skill bundle describes the 'comanda' CLI tool, which enables the execution of declarative AI pipelines. The documentation explicitly states that 'Agentic models' (e.g., `claude-code`, `gemini-cli`) used within `comanda` workflows 'can execute commands, edit files, and interact with the filesystem'. Additionally, workflows can fetch input from arbitrary URLs and reference environment variables. These capabilities, while documented features of the tool, present a significant attack surface for remote code execution (RCE), file system manipulation, and potential data exfiltration if the OpenClaw agent is instructed to process untrusted `comanda` workflows or prompts, classifying it as suspicious due to its high-risk capabilities rather than direct malicious intent.
Capability Assessment
Purpose & Capability
Name/description match the SKILL.md and WORKFLOW-SPEC: this is a user-facing guide for the comanda CLI to generate/visualize/execute YAML workflows that chain LLMs. The skill is instruction-only and therefore does not itself request credentials or binaries; that is consistent because the CLI (installed separately by the user) is what requires API keys.
Instruction Scope
The instructions show workflows reading local files, referencing environment variables, fetching URLs, running shell loops, and using 'agentic' models that can execute commands and edit the filesystem. This is plausible for a workflow engine, but it widens the scope: workflows can access local files and env vars and execute commands, so untrusted workflows could exfiltrate data or run arbitrary commands. The SKILL.md does not itself instruct the platform agent to read unrelated host files, but it documents that comanda workflows can.
Install Mechanism
There is no install spec in the skill (instruction-only). The SKILL.md suggests installing via Homebrew or 'go install' — both are conventional release methods. No downloaded, opaque artifacts are included in the skill bundle.
Credentials
The skill declares no required env vars (reasonable for an instruction-only skill). However, it instructs users to 'comanda configure' to set provider API keys and documents that workflows can reference arbitrary environment variables. That means sensitive credentials will be managed outside this skill by the external CLI; users should expect to supply provider keys locally and be aware that workflows may read environment variables.
Persistence & Privilege
The skill is not always-enabled, is user-invocable, and allows model invocation (the platform default). It does not request persistent system-wide configuration or modify other skills. Autonomous invocation is allowed by default but not combined with 'always:true' or other elevated privileges.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install comanda
  3. After installation, invoke the skill by name or use /comanda
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.2
Add comanda.sh website and GitHub links
v1.0.1
Re-publish to ensure visibility
v1.0.0
Initial release: generate, chart, and process comanda workflows
Metadata
Slug comanda
Version 1.0.2
License
All-time Installs 0
Active Installs 0
Total Versions 3
Frequently Asked Questions

What is Comanda?

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). It is an AI Agent Skill for Claude Code / OpenClaw, with 1982 downloads so far.

How do I install Comanda?

Run "/install comanda" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Comanda free?

Yes, Comanda is completely free (open-source). You can download, install and use it at no cost.

Which platforms does Comanda support?

Comanda is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Comanda?

It is built and maintained by kris-hansen (@kris-hansen); the current version is v1.0.2.

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