Workflow to Skill Converter
What Is It
Convert a workflow with demonstrated usefulness into a reusable skill that a human facilitator and an AI agent can run, inspect, evaluate, and improve. This is not a prompt-polishing exercise.
Why Use It
Local workflows disappear, drift, or spread without their judgment and failure modes. A skill can preserve the productive motion—but packaging an unproven workflow merely scales confusion.
When to Use It
Use after the workflow has a clear outcome, repeated examples, known decisions, and an owner. If the workflow is still unclear or ineffective, map and redesign it first.
What It Produces
- Reuse-readiness decision
- Canonical
SKILL.md, template, and examples
- Context, guardrails, evaluations, and stop rules
- Stewardship, versioning, adoption, and improvement plan
Who Should Participate
Include workflow practitioners, the outcome owner, Product Operations or enablement, an agent-instruction author, and governance partners where consequences require them.
Evidence to Bring
Bring observed workflow examples, before-and-after evidence, decisions and exceptions, context inputs, failures, user feedback, and proof that the practice can be repeated.
How to Do It
- Confirm the workflow changes a useful decision or outcome.
- Assess reuse readiness: repeated use, stable core, known variation, owner, and evidence.
- Extract triggers, inputs, decisions, steps, outputs, handoffs, and completion criteria.
- Preserve judgment: options, tradeoffs, uncertainty, escalation, and stop rules.
- Separate essential instructions from templates, examples, references, and assets.
- Write trigger-rich metadata and concise imperative instructions.
- Add a worked and weak example that demonstrate reasoning.
- Define evaluation scenarios and forward-test without leaking expected answers.
- Assign stewardship, version, review cadence, adoption measures, and retirement rules.
Key Concepts
- Proven before packaged: reusable output requires evidence of a useful motion.
- Judgment preservation: encode decisions, not just steps.
- Progressive disclosure: keep core instructions lean; load details when needed.
- Stewardship: every reusable skill needs an owner and retirement path.
Organizational Applications
Use for discovery, synthesis, portfolio review, evidence review, governance, context assembly, and other recurring product-team motions.
Common Pitfalls
- Converting a blank template or one-off prompt
- Scaling a broken workflow
- Removing anti-patterns to shorten instructions
- Embedding confidential context
- Omitting evaluation, ownership, and retirement
- Measuring downloads instead of changed work or outcomes
Combine With
Use human-aipom-work-contract to define collaboration, aipom-workflow-playbook-builder for a deeper operating playbook, and aipom-adoption-impact-scorecard to measure changed practice.
Assets and Templates
- Conversion template
- Synthetic worked example
- Weak example
Sources
This skill is an original AIPOM synthesis informed by the repository’s canonical skill specification and contribution workflow.
1---2name: workflow-to-skill-converter3description: Convert a proven, improved workflow into a governed, reusable skill with context, decisions, examples, guardrails, evaluations, ownership, and maintenance rules.4---56# Workflow to Skill Converter78## What Is It910Convert a workflow with demonstrated usefulness into a reusable skill that a human facilitator and an AI agent can run, inspect, evaluate, and improve. This is not a prompt-polishing exercise.1112## Why Use It1314Local workflows disappear, drift, or spread without their judgment and failure modes. A skill can preserve the productive motion—but packaging an unproven workflow merely scales confusion.1516## When to Use It1718Use after the workflow has a clear outcome, repeated examples, known decisions, and an owner. If the workflow is still unclear or ineffective, map and redesign it first.1920## What It Produces2122- Reuse-readiness decision23- Canonical `SKILL.md`, template, and examples24- Context, guardrails, evaluations, and stop rules25- Stewardship, versioning, adoption, and improvement plan2627## Who Should Participate2829Include workflow practitioners, the outcome owner, Product Operations or enablement, an agent-instruction author, and governance partners where consequences require them.3031## Evidence to Bring3233Bring observed workflow examples, before-and-after evidence, decisions and exceptions, context inputs, failures, user feedback, and proof that the practice can be repeated.3435## How to Do It36371. Confirm the workflow changes a useful decision or outcome.382. Assess reuse readiness: repeated use, stable core, known variation, owner, and evidence.393. Extract triggers, inputs, decisions, steps, outputs, handoffs, and completion criteria.404. Preserve judgment: options, tradeoffs, uncertainty, escalation, and stop rules.415. Separate essential instructions from templates, examples, references, and assets.426. Write trigger-rich metadata and concise imperative instructions.437. Add a worked and weak example that demonstrate reasoning.448. Define evaluation scenarios and forward-test without leaking expected answers.459. Assign stewardship, version, review cadence, adoption measures, and retirement rules.4647## Key Concepts4849- **Proven before packaged:** reusable output requires evidence of a useful motion.50- **Judgment preservation:** encode decisions, not just steps.51- **Progressive disclosure:** keep core instructions lean; load details when needed.52- **Stewardship:** every reusable skill needs an owner and retirement path.5354## Organizational Applications5556Use for discovery, synthesis, portfolio review, evidence review, governance, context assembly, and other recurring product-team motions.5758## Common Pitfalls5960- Converting a blank template or one-off prompt61- Scaling a broken workflow62- Removing anti-patterns to shorten instructions63- Embedding confidential context64- Omitting evaluation, ownership, and retirement65- Measuring downloads instead of changed work or outcomes6667## Combine With6869Use `human-aipom-work-contract` to define collaboration, `aipom-workflow-playbook-builder` for a deeper operating playbook, and `aipom-adoption-impact-scorecard` to measure changed practice.7071## Assets and Templates7273- [Conversion template](template.md)74- [Synthetic worked example](examples/worked-example.md)75- [Weak example](examples/weak-example.md)7677## Sources7879This skill is an original AIPOM synthesis informed by the repository’s canonical skill specification and contribution workflow.
Dean Peters