pegasus-wrapper — community pegasus-wrapper, pegasus-workflow-toolkit, community, ide skills

v1.0.0

About this Skill

Perfect for DevOps Agents needing automated Pegasus WMS workflow creation with Claude Code integration. Generate a wrapper script for a single Pegasus pipeline step

pegasus-isi pegasus-isi
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Updated: 2/25/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 7/11

This page remains useful for operators, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution Locale and body language aligned
Review Score
7/11
Quality Score
30
Canonical Locale
en
Detected Body Locale
en

Perfect for DevOps Agents needing automated Pegasus WMS workflow creation with Claude Code integration. Generate a wrapper script for a single Pegasus pipeline step

Core Value

Empowers agents to generate reusable toolkits for Pegasus WMS workflows, leveraging Claude Code and shell wrapper scripts, while utilizing templates like wrapper_template.py and wrapper_template.sh.

Ideal Agent Persona

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

Capabilities Granted for pegasus-wrapper

Automating pipeline step wrapper creation
Generating Pegasus WMS workflows with Claude Code
Debugging wrapper scripts using pegasus-templates

! Prerequisites & Limits

  • Requires access to Pegasus.md and pegasus-templates repository
  • Python and shell scripting knowledge recommended
  • Compatibility with Claude Code and Pegasus WMS required

Why this page is reference-only

  • - The underlying skill quality score is below the review floor.

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

After The Review

Decide The Next Action Before You Keep Reading Repository Material

Killer-Skills should not stop at opening repository instructions. It should help you decide whether to install this skill, when to cross-check against trusted collections, and when to move into workflow rollout.

Labs Demo

Browser Sandbox Environment

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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 DevOps Agents needing automated Pegasus WMS workflow creation with Claude Code integration. Generate a wrapper script for a single Pegasus pipeline step

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 pipeline step wrapper creation, Generating Pegasus WMS workflows with Claude Code, Debugging wrapper scripts using pegasus-templates.

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 repository. Python and shell scripting knowledge recommended. Compatibility with Claude Code and Pegasus WMS required.

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.

! Reference-Only Mode

This page remains useful for installation and reference, but Killer-Skills no longer treats it as a primary indexable landing page. Read the review above before relying on the upstream repository instructions.

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

pegasus-wrapper

Install pegasus-wrapper, an AI agent skill for AI agent workflows and automation. Review the use cases, limitations, and setup path before rollout.

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

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:

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