research-ideation

What this skill does

# Research Ideation

From research goal to ranked ideas and a detailed proposal.

```
Step 0: Load evo-memory (M_I)
    ↓
Step 1: Define Goal
    ↓
Step 2: Literature Grounding (MUST use paper-navigator scripts)
    ↓
Step 3: Generate Ideas (3 directions × 3 personas)
    ↓
Step 4: Refine Ideas (3 tracks × N iterations)
    ↓
Step 5: ELO Tournament → Present Top-3 to User
    ↓
Step 6: Update evo-memory (IDE)
    ↓
User Selects
    ↓
Step 7: Expand into Proposal
    ↓
Step 8: Validate and Iterate
```

## When to Use

- User wants to find a research direction or brainstorm research ideas
- User wants to evaluate whether an idea is novel or worth pursuing
- User wants to rank or compare multiple research ideas
- User wants to generate a research proposal from an idea

## When NOT to Use

- **Finding/reading papers** → use `paper-navigator`
- **Literature survey report** → use `research-survey`
- **Planning a paper (story design, experiment plan)** → use `paper-planning`

---

## Step 0: Load Prior Knowledge from evo-memory

**Before any ideation begins**, load Ideation Memory (M_I) from prior research cycles:

1. Read M_I at `/memory/ideation-memory.md` (refer to `evo-memory` skill)
2. Select the **top-2 entries** (k_I=2) most relevant to the user's current goal by comparing each entry's Summary and Retrieval Tags against the goal
3. **Feasible directions** from prior cycles → use as seeds in Step 3 (incorporate as candidate research directions alongside new ones)
4. **Unsuccessful directions** marked as fundamental failures → use during idea pruning in Step 4 (prune any idea that matches a fundamental failure pattern)
5. If M_I doesn't exist yet (first cycle), skip this step

This step prevents repeating known dead ends and builds on prior successes across research cycles.

## Step 1: Define a Long-Term Research Goal

Start with a goal that has both scientific and practical value. Ambitious enough for multiple papers, concrete enough to guide daily decisions.

Ask: "What is the ultimate form of this research direction? What would the world look like if this problem were fully solved?"

## Step 2: Literature Grounding (via paper-navigator)

**Invoke `paper-navigator`** (Workflow 9: Ideation Support) to collect 30-50 relevant papers. Do NOT skip this step or substitute with general knowledge — ideas must be grounded in real papers.

**CRITICAL: All paper discovery in this step MUST use the `paper-navigator` skill and its scripts (scholar_search, citation_traverse, arxiv_monitor, recommend, etc.). Using WebSearch, WebFetch, or any generic web search tool for finding papers is PROHIBITED.** Generic web search returns blog posts, news articles, and low-quality results — only paper-navigator provides access to Semantic Scholar, arXiv, citation graph traversal, and academic recommendations needed for rigorous literature grounding.

### Build Challenge-Insight Tree

From the collected papers, construct a **challenge-insight tree** — a many-to-many mapping between technical challenges and the insights/techniques that address them:

- **Extract challenges**: From each paper, what technical problem does it solve?
- **Extract insights**: What technique or key idea does it use?
- **Map connections**: Which insights address which challenges?

**How this drives ideation**:
- Challenges with few insights → **unsolved problem** (candidate for Step 3)
- Insights not yet applied to a challenge → **cross-domain transfer opportunity** (candidate for Step 4)
- Challenges with many insights → well-studied, avoid unless you have a fundamentally new angle

Also generate a condensed **literature review synthesis** as context for idea generation (for full surveys use `research-survey`).

See `references/literature-tree.md` for construction methodology.

**Execution rule**: Do NOT generate ideas without real paper grounding. The tree must reference actual papers with titles, authors, and findings. Paper search MUST go through `paper-navigator` — never use WebSearch/WebFetch as a shortcut.

## Step 3: Generate Ideas

Generate 3 initial research ideas from 3 distinct research directions, grounded in the literature.

### Three Personas

| Persona | Focus |
|---------|-------|
| **Innovator** | Novelty & creativity — groundbreaking, high-risk/high-reward |
| **Pragmatist** | Feasibility — realistic, clearly executable |
| **Critic** | Scientific value — advances understanding, rigorous |

### Process

1. Analyze literature + challenge-insight tree → identify 3 fundamentally different research directions
2. Generate one idea per direction using **Innovator** persona
3. Each idea must follow one of two methodological paths:
   - **Path 1 (Focused Contribution)**: Single new component; clean hypothesis
   - **Path 2 (System Contribution)**: Tight causal interaction between components; emergent capability

### Idea Format

```
# Research Idea: [Concise Title]

## Core Idea
[One paragraph: the proposal + which research direction it addresses]

## Validation Plan
[Concrete experiment outline: datasets, baselines, metrics]
```

## Step 4: Refine Ideas

Run 3 parallel refinement tracks — one per initial idea. Each track uses all 3 personas.

```
For each track:
  For N=3 iterations:
    1. Evaluate current best idea (novelty, feasibility, impact, alignment)
    2. All 3 personas generate refined versions based on evaluation
    3. Pick the best refinement as seed for next iteration
  Track champion = best idea across iterations
```

### 5 Evolution Strategies

1. **Enhancement through Grounding**: Strengthen with literature citations
2. **Improving Coherence**: Fix logical flaws in the mechanism
3. **Inspiration and Combination**: Combine with a different concept from literature
4. **Simplification**: Strip down to a clean, testable hypothesis
5. **Literature-Driven Pivot**: Abandon the mechanism; propose a new approach from literature

**Critical rule**: If evaluation says the approach is a dead-end, the persona MUST pivot — refinement is not restricted to patching.

### Logical Cohesion Principles

- **Too many variables** → Focus via Subtraction: isolate the most promising variable
- **Disconnected components** → Justify via Strong Correlation: build explicit causal links

## Step 5: ELO Tournament → Present Top-3

Rank all track champions through pairwise comparison, then **present the top-3 to the user for selection**.

### Four Dimensions

| Dimension | What It Measures |
|-----------|-----------------|
| **Novelty** | How different from existing published work? |
| **Feasibility** | Can this be implemented within reasonable resources? |
| **Relevance** | Does this address an important problem aligned with the goal? |
| **Clarity** | Is the idea well-defined enough to start immediately? |

### Tournament

- **Starting Elo**: 1500 | **K-factor**: 32
- Compare ideas pairwise → update Elo → sort by final score
- See `references/elo-ranking-guide.md` for rubric and formula

### Present Top-3 to User

After the tournament, present the top-3 ideas with **both** a comparison table and the **full refined idea** for each. This ensures the user sees the concrete, actionable version of each idea — not just a summary.

#### Part 1: Comparison Table

```
## Top-3 Research Ideas (ranked by ELO)

| Rank | Title | Core Mechanism | Novelty | Feasibility | Relevance | Clarity | ELO |
|------|-------|---------------|---------|-------------|-----------|---------|-----|
| 1 | ... | ... | 9 | 7 | 8 | 8 | 1280 |
| 2 | ... | ... | 7 | 9 | 8 | 7 | 1240 |
| 3 | ... | ... | 8 | 6 | 9 | 7 | 1210 |
```

#### Part 2: Full Refined Ideas

For **each** of the top-3, present the refined idea using the same structured format as Step 3, plus a refinement summary:

```
# Refined Idea [Rank]: [Concise Title]

## Core Idea
[One paragraph: the refined proposal — this should reflect ALL changes from Step 4 refinement,
not the original Step 3 version]

## Validation Plan
[Concrete experiment outline updated with refinement