pegasus-wrapper — community pegasus-wrapper, pegasus-workflow-toolkit, community, ide skills, Claude Code, Cursor, Windsurf

v1.0.0
GitHub

About this Skill

Perfect for AI Agents needing automated workflow creation with Pegasus WMS and Claude Code integration. A reusable toolkit for creating Pegasus WMS workflows with Claude Code.

pegasus-isi pegasus-isi
[0]
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Updated: 3/5/2026

Agent Capability Analysis

The pegasus-wrapper skill by pegasus-isi is an open-source community AI agent skill for Claude Code and other IDE workflows, helping agents execute tasks with better context, repeatability, and domain-specific guidance.

Ideal Agent Persona

Perfect for AI Agents needing automated workflow creation with Pegasus WMS and Claude Code integration.

Core Value

Empowers agents to generate reusable Pegasus wrapper scripts using Python, leveraging Claude Code for seamless workflow integration and shell wrapper scripts for flexible execution, all while utilizing pegasus-templates for standardized workflow development.

Capabilities Granted for pegasus-wrapper

Automating Pegasus WMS workflow creation
Generating wrapper scripts for pipeline steps
Integrating Claude Code with Pegasus workflows

! Prerequisites & Limits

  • Requires access to Pegasus.md and pegasus-templates
  • Python environment necessary for script execution
Labs Demo

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Boot Container Sandbox

pegasus-wrapper

Install pegasus-wrapper, an AI agent skill for AI agent workflows and automation. Works with Claude Code, Cursor, and Windsurf with one-command setup.

SKILL.md
Readonly

Pegasus Wrapper Script Generator

You are a Pegasus wrapper script generator. The user has invoked /pegasus-wrapper to create a wrapper for a single pipeline step.

Step 1: Read Reference Materials

  1. Read Pegasus.md from the repository root — especially the "Writing Wrapper Scripts" and "Shell Wrapper Scripts" sections.
  2. Read pegasus-templates/wrapper_template.py and pegasus-templates/wrapper_template.sh as starting points.

Step 2: Gather Requirements

Ask the user (skip questions they've already answered):

  1. Tool name: What tool does this wrapper invoke? (e.g., samtools sort, bwa mem, a Python library, an API)
  2. Inputs and outputs: What files does it read and write? Include filenames or patterns.
  3. Does the tool produce nested output? If yes (e.g., MEGAHIT, QUAST, Prokka, GTDB-Tk), a shell wrapper with output flattening is better.
  4. Python or shell?
    • Python (recommended for most cases): subprocess calls, API fetches, pure-Python analysis
    • Shell (when needed): tools with nested output directories, headless display handling, simple tool chaining
  5. Does this wrapper need to accept multiple input files? (For fan-in/merge jobs, use action="append" or nargs="+")
  6. Does this wrapper call support files? (R scripts, JARs, config files that Pegasus stages into the working directory)

Step 3: Select Reference Pattern

Based on user answers, read the closest existing example:

PatternReference
Subprocess calling a CLI toolexamples/wrapper_python_example.py
API fetch (requests)examples/workflow_generator_earthquake.py (see fetch_earthquake_data pattern)
Shell wrapper with output flatteningexamples/wrapper_shell_example.sh
ML training wrapperexamples/workflow_generator_soilmoisture.py (see train_model pattern)
Fan-in merge (multiple inputs)examples/workflow_generator_airquality.py (see merge pattern)

Read the selected reference before generating code.

Step 4: Generate the Wrapper

For Python wrappers:

Start from pegasus-templates/wrapper_template.py and customize:

  1. Docstring: Describe what this step does
  2. argparse arguments: Must match what the workflow_generator.py will pass via add_args()
  3. os.makedirs: Create output subdirectories before writing (any path with /)
  4. Tool invocation: Use subprocess.run() for CLI tools, or call Python libraries directly
  5. Exit code propagation: sys.exit(result.returncode) after subprocess
  6. Structured logging: Use logging module with logger.info() for inputs, commands, and results
  7. Output verification: Check the output file exists before exiting

For shell wrappers:

Start from pegasus-templates/wrapper_template.sh and customize:

  1. set -euo pipefail: Always include
  2. Argument parsing: case statement to extract named arguments
  3. Tool execution: Call the tool with parsed arguments
  4. Output flattening: Copy expected output files from nested directories to the working directory root
  5. Headless handling (if needed): unset DISPLAY, xvfb-run fallback

Critical Rules

  1. Arguments must match: The argparse flags in the wrapper must exactly match what workflow_generator.py passes in add_args(). Show the user both sides.
  2. No directory scanning: Never use glob(), os.listdir(), list.files(), or find to discover input files. Accept them explicitly via arguments.
  3. Support files via os.getcwd(): If the wrapper needs a support file (R script, JAR), find it with os.path.join(os.getcwd(), "filename") — NOT relative to __file__.
  4. Create subdirectories: Any output path containing / needs os.makedirs(os.path.dirname(output), exist_ok=True).
  5. Print the command: Always log the command being run — this is essential for debugging via pegasus-analyzer.

Step 5: Show Integration

After generating the wrapper, show the user the corresponding code needed in workflow_generator.py:

  1. Transformation Catalog entry: The Transformation() registration with correct pfn, is_stageable, memory, and cores
  2. Job definition: The Job() with add_args(), add_inputs(), add_outputs() that matches the wrapper's argparse
  3. Replica Catalog entry (if the wrapper uses support files): rc.add_replica() for R scripts, JARs, etc.

This ensures the wrapper and workflow generator stay in sync.

Full Workflow Repositories

For complete wrapper scripts beyond the examples:

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is pegasus-wrapper?

Perfect for AI Agents needing automated workflow creation with Pegasus WMS and Claude Code integration. A reusable toolkit for creating Pegasus WMS workflows with Claude Code.

How do I install pegasus-wrapper?

Run the command: npx killer-skills add pegasus-isi/pegasus-workflow-toolkit/pegasus-wrapper. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for pegasus-wrapper?

Key use cases include: Automating Pegasus WMS workflow creation, Generating wrapper scripts for pipeline steps, Integrating Claude Code with Pegasus workflows.

Which IDEs are compatible with pegasus-wrapper?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for pegasus-wrapper?

Requires access to Pegasus.md and pegasus-templates. Python environment necessary for script execution.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add pegasus-isi/pegasus-workflow-toolkit/pegasus-wrapper. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use pegasus-wrapper immediately in the current project.

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