UiPath Boost

Learning and communication

You invoke it

uipath-training-lab-scaffolder

Use only when the user explicitly asks to scaffold and validate a consistent UiPath training lab from an approved curriculum.

Install this skill

Claude Code

npx skills add 1aifanatic/uipath-boost --skill uipath-training-lab-scaffolder --agent claude-code --global --yes

Codex

npx skills add 1aifanatic/uipath-boost --skill uipath-training-lab-scaffolder --agent codex --global --yes

Create a navigable, non-empty lab skeleton that makes learner tasks, reference implementations, fixtures, prerequisites, and verification conventions predictable across a course.

Maturity: pilot.

Ownership Boundary

This custom skill owns: Create a navigable, non-empty lab skeleton that makes learner tasks, reference implementations, fixtures, prerequisites, and verification conventions predictable across a course.

Keep current product commands, schemas, artifact validation, live tenant operations, and policy administration with official UiPath skills.

Workflow

1. Parse the curriculum

Extract ordered sections, exercises, variants, objectives, prerequisites, expected artifacts, and which exercises need UiPath projects or only conceptual material.

Completion criterion: Every planned exercise has a unique position and purpose.

2. Create the structure

Use the bundled scaffolder with a reviewed JSON plan to create numbered section and exercise directories and requested problem, solution, explainer, fixture, and reference variants.

Completion criterion: The directory tree matches the approved plan.

3. Write meaningful stubs

Populate each README with the exercise title, objective, learner task or explanation purpose, expected evidence, prerequisites, and completion signal. Do not use empty placeholders.

Completion criterion: Every primary variant is understandable without instructor narration.

4. Add UiPath-specific pointers

For project exercises, state the artifact type, official skill owner, sample-data policy, setup prerequisites, and validation expectations without fabricating product files.

Completion criterion: Learners know how the lab connects to current UiPath tooling.

5. Validate the scaffold

Check naming, ordering, required variants, non-empty files, duplicate identifiers, broken internal links, and plan-to-tree completeness.

Completion criterion: The scaffold passes deterministic structural validation.

6. Hand off authoring

List the exercises that still need real project assets, solutions, diagrams, recordings, or test data and assign the next authoring route.

Completion criterion: The skeleton is ready for content development rather than mistaken for a finished course.

Output Contract

  • Numbered lab directory tree.
  • Meaningful exercise README stubs.
  • Structural validation report.
  • Remaining content-authoring backlog.

Guardrails

  • Do not create empty README files or meaningless placeholder-only stubs.
  • Do not invent working UiPath project assets when the request is only scaffolding.
  • Do not expose solution content inside problem variants.
  • Do not renumber existing exercises without preserving references and history.

Example Requests

  • "Scaffold a ten-module UiPath Agent Builder course."
  • "Create problem and solution folders for RPA exercises."
  • "Generate a workshop lab skeleton from this lesson plan."

Finish

Report completed work, observed evidence, the next official owner, and every blocker. Mark unobserved actions as pending.

Files this skill uses

Synced from 1aifanatic/uipath-boost@8a9791b on 2026-08-06. Independent community project. UiPath's official skills remain the source of truth for product commands, schemas, deployment, and platform behavior.
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