jeonnoin-alt Research Ideation
Overview
Generate concrete research ideas from loose inputs — keywords, datasets, papers — and present them with actionable metadata. This skill is divergent: it expands possibilities. Its downstream partner research-brainstorming is convergent: it narrows one idea into a rigorous study design.
Core principle: You cannot refine a question you haven't asked yet. Ideation comes before design.
When to Use
Use this skill when:
- The user has no formed research question — only keywords, a dataset, or vague interest
- The user says "what should I research?", "what can I do with this data?", "research ideas for [topic]"
- A dataset or paper is provided without a specific question attached
whats-nextdiagnoses the state as Pre-ideation
Do NOT use this skill when:
- The user already has a research question (e.g., "Does X cause Y?") → use
research-brainstorming - The user has a hypothesis to test → use
hypothesis-first - The user is stuck mid-project → use
whats-next
Discriminating rule: If the user can state their interest as "Does/Is/Can [X] [verb] [Y]?", they have a formed question → skip to research-brainstorming. If they cannot, they are in ideation territory.
Checklist (Step Order Fixed)
You MUST create a task for each of these items and complete them in order:
- Collect inputs — gather keywords/datasets/papers from conversation or by asking
- Explore sources — analyze what's available
- Generate ideas — 3-5 by default; 5-10 if scope is broad
- Present ideas — each with title + description + metadata table
- Recommend and propose — highlight one + suggest
research-brainstorminghandoff
Step 1: Collect Inputs
The skill accepts three types of input. All optional, but at least one must be present:
- Keywords / interest area — e.g., "attention mechanism", "neuroimaging", "time-series forecasting"
- Dataset — files in the project (csv, npy, etc.) whose structure the agent explores
- Papers / literature — user-provided PDFs, URLs, or web search for recent trends
Collection rules:
- Check what the user already provided in conversation. Skip what's already known.
- If nothing is provided, ask once: "Are there datasets or papers I should look at? Or just throw me some keywords."
- Minimum requirement: one keyword. The skill can start from a single keyword alone.
- Do NOT ask multiple questions. One prompt, then start working.
Step 2: Explore Sources
Adapt exploration to the input types available:
| Input type | What to do |
|---|---|
| Dataset | Read the file(s). Analyze columns, shape, dtypes, descriptive stats (N, mean, std, NaN rate, label distribution). Note what variables are available and what relationships could be studied. |
| Paper | Read abstract + methodology + limitations. Extract the research question, key findings, and identified gaps. Note what the authors suggest for future work. |
| Keywords | Web-search for recent trends, open problems, and active debates in the area. Look for survey papers, workshop topics, and recent preprints. |
When multiple input types are present, look for cross-pollination — where dataset characteristics meet literature gaps or keyword trends.
Step 3: Generate Ideas
Default: 3-5 ideas. If the agent judges the scope is broad (multiple fields, large dataset with many variables, or diverse literature), expand to 5-10 ideas without asking.
Each idea should be:
- Concrete — specific enough that
research-brainstormingcould start refining it - Distinct — ideas should not be minor variations of each other
- Grounded — connected to the actual inputs (data available, literature gap identified, trend observed)
Step 4: Present Ideas
Each idea follows this template:
N. [Idea Title]
[2-3 sentences: why this is interesting, what gap it fills]
| Item | Detail |
|---|---|
| Difficulty | High / Medium / Low |
| Data needed | Already available / Additional collection required / Public dataset available |
| Estimated duration | ~2 weeks / ~1 month / ~3 months (one researcher, full-time, excluding data collection) |
| Core methodology | e.g., "transformer + EEG temporal features" |
Step 5: Recommend and Propose
After presenting all ideas, recommend one:
"I find #N most promising — [one-sentence reason]. Want to start
research-brainstormingto shape this into a rigorous study design?"
The user may:
- Pick the recommended idea → invoke
research-brainstorming - Pick a different idea → invoke
research-brainstormingwith that idea - Ask for more ideas → generate additional ideas
- End the session → suggest journaling (see Session End below)
All are valid outcomes. The handoff is a suggestion, never a forced transition.
Session End Behavior
If the user ends the session without picking an idea:
"Want me to save these ideas before we wrap up?
research-journalcan capture them so you don't lose them."
This is a gentle suggestion. Ideas are ephemeral by default — saved only if the user journals or picks one to develop.
Anti-Patterns
| What you might do wrong | What to do instead |
|---|---|
| Start designing a study for one of the ideas | Stop. That's research-brainstorming's job. Present ideas, don't refine them. |
| Generate only one idea | Always generate at least 3. The user needs options. |
| Ask 5 questions before generating | Collect inputs in one prompt, then work. |
| Force the user to pick an idea | Present, recommend, wait. The user decides. |
| Generate ideas unrelated to the inputs | Every idea must connect to at least one input (keyword, dataset feature, or literature gap). |
| Skip exploring the dataset | If a dataset is provided, you MUST look at its structure. Don't ideate in the abstract. |
Integration
- Called by:
eureka:using-eureka(when no formed question exists),eureka:whats-next(Pre-ideation diagnosis) - Hands off to:
eureka:research-brainstorming(when user selects an idea — suggestion only) - Does NOT invoke:
hypothesis-first,experiment-design, or any execution/review skill
Skill Type
FLEXIBLE — The step order (collect → explore → generate → present → recommend) is fixed and must not be skipped. But how each step executes adapts to context:
- Dataset-heavy input → more structural analysis, fewer web searches
- Keyword-only input → heavier web search for trends and gaps
- Broad field → 5-10 ideas; narrow niche → 3-5 ideas
No scientific integrity is at stake at the ideation phase. The downstream rigid skills (hypothesis-first, claims-audit) enforce that discipline later.