maf-prs-job Skill
Convert an existing Prompt Flow Parallel Run Step (PRS) pipeline submission into an Azure ML PRS pipeline that runs a Microsoft Agent Framework (MAF) workflow. Wraps the MAF workflow into a PRS init()/run() entry script, generates the parallel component YAML and conda environment, and rewrites the pipeline submission s Published by microsoft in promptflow.
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Developers using promptflow, Includes SKILL.md, Reusable instructions
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Copy skill directory
2 months ago · MIT license
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What is maf-prs-job Skill?
Convert an existing Prompt Flow Parallel Run Step (PRS) pipeline submission into an Azure ML PRS pipeline that runs a Microsoft Agent Framework (MAF) workflow. Wraps the MAF workflow into a PRS init()/run() entry script, generates the parallel component YAML and conda environment, and rewrites the pipeline submission s Published by microsoft in promptflow. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.
Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement. See how SkillIndex evaluates profiles.
Key capabilities
- Includes SKILL.md support
- Reusable instructions support
- Developers using promptflow
Declared skill metadata
- Declared author: Team
- Declared license: MIT
- Source file: .github/skills/maf-prs-job/SKILL.md
These fields retain source and confidence evidence from the indexed SKILL.md.
Compatibility and setup
- Install or run with Copy skill directory
When to use maf-prs-job Skill
- Use it for developers using promptflow.
Built with
Editorial notes
Source
- Creator: microsoft
- Repository: microsoft/promptflow
- Skill file: .github/skills/maf-prs-job/SKILL.md
What it does
Convert an existing Prompt Flow Parallel Run Step (PRS) pipeline submission into an Azure ML PRS pipeline that runs a Microsoft Agent Framework (MAF) workflow. Wraps the MAF workflow into a PRS init()/run() entry script, generates the parallel component YAML and conda environment, and rewrites the pipeline submission s
Skill instructions
Prompt Flow PRS → MAF PRS Pipeline Conversion Convert an existing Prompt Flow Parallel Run Step (PRS) pipeline submission (one that uses loadcomponent("flow.dag.yaml")) into a PRS pipeline that runs a Microsoft Agent Framework (MAF) workflow as the parallel component. What loadcomponent(flow.dag.yaml) did automatically — and which pieces this skill produces by hand — is documented in references/pf-vs-maf-prs.md §0. Triggers Activate this skill when the user wants to: - Convert a Prompt Flow PRS pipeline submission to use a MAF workflow instead. - Run a MAF workflow as a parallel / bulk job on AML compute. - Replace loadcomponent(flow.dag.yaml) with a hand-built parallel component that wraps a MAF workflow. Also activate on these PF-user phrasings (people who learned from the run-flow-with-pipeline notebook will describe their need in PF terms): - "How do I loadcomponent a MAF workflow?" / "loadcomponent('workflow.py') doesn't work — what's the right way?" - "Give me the MAF equivalent
Verified compatibility and discovery
Frequently asked questions
What is maf-prs-job?
maf-prs-job is a open-source AI agent skill with Copy skill directory. Convert an existing Prompt Flow Parallel Run Step (PRS) pipeline submission into an Azure ML PRS pipeline that runs a Microsoft Agent Framework (MAF) workflow.
Who is maf-prs-job best for?
maf-prs-job is best for reusing agent instructions, scripts, and references.
How do I install maf-prs-job?
Install or run maf-prs-job using Copy skill directory. Check maf-prs-job for the latest setup command.
Is maf-prs-job actively maintained?
maf-prs-job may need a closer maintenance check before production use.
Project health auto-fetched from the source repository.
Maintain this resource?
Review this source-backed profile, send a correction with evidence, or link to it from your documentation. Claims verify your relationship to the project; profile facts still require source evidence and editorial review.
