# Project Innovation Engine

> Designs original, feasible, pedagogically rich computing projects and exam scenarios that are hard to find pre-made online. Use when an instructor wants fresh project ideas, novel machine exams, or multi-stage project concepts.

- Skill: `alainlebret/project-innovation-engine` (Agent Skill)
- Install (CLI): `npx skillmds@latest add alainlebret/project-innovation-engine`
- Raw SKILL.md: https://api.skillmd.com/api/skills/alainlebret/project-innovation-engine/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: alainlebret (https://skillmd.com/u/alainlebret)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/alainlebret/project-innovation-engine

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# Project Innovation Engine

## Goal

Generate computing project or exam ideas that are:
- **Original** — not trivially found on GitHub, LeetCode, or standard textbooks
- **Feasible** — completable by the target cohort within the stated duration
- **Pedagogically rich** — exercise multiple learning outcomes, not just one

## When to use

- When `mission.json → evaluation_mode` is `project` and the instructor has no topic yet.
- When a machine exam needs a fresh scenario that students cannot Google.
- When a fil rouge project must span multiple milestones across a semester.

## Inputs

- `mission.json` — level, domain, duration, learning_outcomes, constraints
- Optionally: list of topics already used in previous years (to avoid repetition)

## Output contract

| File | Description |
|---|---|
| `project-ideas.md` | 3–5 fully described project concepts with rationale |
| `selected-concept.md` | The recommended concept developed in detail (chosen from project-ideas.md) |

### `project-ideas.md` format per concept

```markdown
## Concept N — <Title>

**Domain:** <sector>
**Difficulty:** <level> — estimated <X>h per student
**Novel element:** <what makes this hard to find pre-made>

### Description
<2-3 paragraph narrative>

### Learning outcomes covered
- [outcome from mission.json]
- ...

### Milestones (if project spans multiple sessions)
1. <milestone 1> — <deliverable> — <week>
2. ...

### Anti-cheat properties
<Why copying from the internet is hard: unique scenario, custom data format, specific API constraints, etc.>

### Risks
<Known difficulties that could block students; suggested mitigation>
```

## Novelty strategies

Use one or more of the following to generate original scenarios:
- **Cross-domain combination**: embed a computing problem in an unusual domain (e.g. scheduling problem framed as a space mission constraint solver)
- **Inverted role**: students implement the grader, not the solution (meta-programming, AST analysis)
- **Custom protocol**: invent a simple domain-specific binary or text protocol students must parse and generate
- **Constrained resources**: add a novel constraint (memory cap, no external libraries, fixed number of system calls)
- **Multi-agent coordination**: require two student programs to cooperate via IPC or network

## Rules

- Propose at least one concept that can be completed in the stated `duration` with a 20 % safety margin.
- Flag any concept where the reference solution would take more than 4 hours for an expert — it is likely too complex.
- Do not propose concepts that require licences, proprietary tools, or hardware students may not have.
- Each concept must map its tasks to specific `learning_outcomes` from `mission.json`.