Create a complete Pegasus workflow project from a pipeline description
Generate a wrapper script for a single Pegasus pipeline step
Generate a Kiso experiment.yml configuration file for running Pegasus workflows or shell experiments on cloud/edge/local testbeds. Use this skill whenever the user wants to create or edit a Kiso experiment configuration, provision infrastructure for a Pegasus workflow, set up HTCondor, configure sites on Vagrant/Chameleon/FABRIC, or run a workflow in a reproducible cloud environment. Trigger on: "create experiment.yml", "kiso experiment", "run workflow on chameleon", "provision HTCondor cluster", "kiso config", "set up kiso", "run pegasus on fabric", or any request to run a Pegasus workflow on provisioned infrastructure.
Convert a Snakemake or Nextflow pipeline to a Pegasus workflow
Diagnose Pegasus workflow failures from error messages and logs
External network access
Connects to servers outside your machine
A curated collection of Claude Code plugins for scientific computing — built for researchers and developers working with Pegasus WMS and SciTech infrastructure.
Claude Code plugins extend the Claude Code CLI with domain-specific skills, MCP servers, and AI-assisted workflows. This marketplace provides plugins tailored for scientific computing — including Pegasus WMS workflow authoring and SciTech project development.
Add the marketplace and install a plugin in two commands:
/plugin marketplace add pegasus-isi/claude-plugin-marketplace
/plugin install <plugin-name>@scitech
Run the following commands from within Claude Code:
/plugin marketplace add pegasus-isi/claude-plugin-marketplace
/plugin install <plugin-name>@scitech
Add the following to your .claude/settings.json file:
{
"extraKnownMarketplaces": {
"scitech": {
"source": {
"source": "github",
"repo": "pegasus-isi/claude-plugin-marketplace"
}
}
},
"enabledPlugins": {
"<plugin-name>@scitech": true
}
}
| Plugin | Description |
|---|---|
| pegasus-dev | Skills and tools for developing software on SciTech projects — git workflows, code review, commit conventions, and project-specific best practices. |
| pegasus-ai | Workflow authoring for Pegasus WMS — generate workflow.yml files, experiment configs, and scaffold scientific pipelines with Claude. |
| impeccable | Design vocabulary and skills for frontend development. Includes 20 commands (/polish, /distill, /audit, /typeset, /overdrive, etc.) and an enhanced frontend-design skill with curated anti-patterns. |
| nano-banana | Nano Banana image generation supporting Gemini Flash, Pro, and Nano Banana 2 models. |
See CONTRIBUTING.md for instructions on how to add or update plugins.
Funded by National Science Foundation (NSF) under award 2513101.
Apache 2.0 © Pegasus ISI
Based on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
npx claudepluginhub pegasus-isi/claude-plugin-marketplace --plugin pegasus-aiJARVIS-CD MCP with a compact user pipeline contract and explicit admin compatibility profiles
Orchestrate complex workflows with DAG-based execution, parallel tasks, and run history tracking
Pi Flow — author, enhance, and run structured filesystem-coordinated workflows (a DAG of producer/verify nodes) as a fleet of efficient pi agents driven by non-Claude coding-plan models, with Claude Code as the single console. Three skills: piflow-init (create a workflow), piflow-enhance (improve it), piflow-start (run + monitor it).
Dagu workflow orchestration: workflow authoring, web UI, and REST API
A Claude plugin for software development on SciTech projects.
High-intelligence Claude Code copilot with deep code reasoning, evidence-driven planning, orchestration-first execution, model routing, context budgeting, CI/CD integration, enterprise security, plugin development, prompt engineering, performance profiling, agent teams, channels (event-driven autonomy with CI webhook, mobile approval relay, Discord bridge, and fakechat dev profile), interactive tutorials, LSP integration, security-hardened hook script library, MCP Prompts coverage, common workflow packs, runtime selection guide, computer-use patterns, checkpointing, scheduled-task blueprints, repo bootstrap scanner, hook policy engine (8 installable packs), layered memory deployment, role-based subagent packs (implementer, debugger, migration-lead, dependency-auditor, release-coordinator), 5 agent-team topology kits, autonomy operating mode (4 profiles + 3 gates), and a queryable 15-tool MCP documentation server with autonomy advisor.
Structured AI-enabled research workflows for software development: Research, Plan, Experiment, Implement
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