Agent skill

research-ideation

Guides research ideation through a 5-step goal-driven workflow: define long-term goal, build literature tree (novelty + challenge-insight), select a problem (well-established solution check), design a solution (cross-domain transfer + decomposition), validate and iterate. Also covers structured paper reading (3 depth levels). Use when: user wants to find a research direction, brainstorm ideas, build field vision, do a literature review, evaluate idea novelty, or read papers systematically. Do NOT use for comparing/ranking existing ideas (use idea-tournament) or planning a paper (use paper-planning).

Stars 141
Forks 17

Install this agent skill to your Project

npx add-skill https://github.com/EvoScientist/EvoSkills/tree/main/skills/research-ideation

Metadata

Additional technical details for this skill

tags
core research ideation literature
author
EvoScientist
version
1.0.0

SKILL.md

Research Ideation

A goal-driven workflow for finding important research problems, designing novel solutions, and building deep field understanding through structured paper reading.

When to Use This Skill

  • User wants to find a research direction or brainstorm research ideas
  • User needs to do a literature review or map a research field
  • User asks about evaluating whether an idea is novel or worth pursuing
  • User wants to read papers more effectively or build a systematic reading habit
  • User mentions "research ideation", "find a problem", "literature tree", "novelty check", "paper reading"

Goal-Driven Research Workflow

Follow these five steps in order. Each step builds on the previous one.

Step 1: Define a Long-Term Research Goal

Start with a goal that has both scientific and practical value. The goal should be ambitious enough to sustain multiple papers, but 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: Build a Literature Tree

Map the field by constructing two complementary trees:

  • Novelty tree: Classify existing work by milestone tasks, representative pipelines, and novel modules. This reveals WHERE the field has gaps.
  • Challenge-insight tree: Collect technical challenges and the insights/techniques that address them. This reveals WHICH problems lack good solutions.

See references/literature-tree.md for the full construction method and four types of novelty.

Step 3: Select a Problem

Find tasks with genuine research space. The key question: "Is this problem worth solving, or has a well-established solution already claimed this territory?"

Use the well-established solution check (4 levels) to decide whether to proceed or switch problems. Actively seek new failure cases rather than improving on known benchmarks.

See references/problem-selection.md for the full selection framework.

Step 4: Design a Solution

Novel techniques are creative combinations of existing methods, not simple concatenations. Use two design patterns:

  • Cross-domain transfer: Find papers in completely different domains that solve a technically similar problem, then adapt their solution.
  • Problem decomposition: Break the problem into sub-problems, solve each via cross-domain transfer, then combine.

See references/solution-design.md for the full design methodology and knowledge distillation pipeline.

Step 5: Validate and Iterate

Run experiments on representative data. Use results to refine your understanding. If the approach fails, return to Step 3 or Step 4 with updated knowledge from the failure.

Output artifacts: Research direction summary (problem statement, proposed approach, novelty claim, key risks) — this becomes the input to idea-tournament or paper-planning.

See the experiment-craft skill for systematic debugging when experiments don't work as expected.

Counterintuitive Ideation Rules

Prioritize these rules before regular ideation:

  1. Problem selection matters more than solution design: Choosing WHAT to solve has more impact than HOW you solve it. A great solution to an unimportant problem is still unimportant.
  2. Pursue new failure cases, not incremental improvements: Don't improve a technique on its original setting. Find new settings where it breaks — new failure cases on new data are contributions even if the technique itself isn't novel.
  3. If a well-established solution exists, switch problems: Solving an already-solved problem wastes time regardless of your angle. Improvement space is too small.
  4. Technology is creative combination, not concatenation: Novel techniques combine existing methods in non-obvious ways. Simple A-to-B pipelines are not contributions — if direct concatenation worked, the problem would have no technical challenge.
  5. When a breakthrough tool appears, apply it to YOUR roadmap: Don't improve the tool itself on its original benchmarks. Use it to solve YOUR milestone tasks — this produces high-impact work because you combine the tool's power with your domain expertise.
  6. A paper without real contribution wastes your time: Even if accepted, it doesn't advance the field or earn respect. Do work that genuinely moves the needle.

Structured Paper Reading

Turn reading into structured Q&A using a paper parsing tree. Three levels of depth:

Level Goal What You Can Do After
1. Technical Understand all details and terminology Reproduce the method; explain each component
2. Analytical Know what problem it solves and why this approach Explain the paper's motivation and design choices
3. Contextual Know its position in the literature tree Update your field map; generate new research questions

Write a structured summary for every paper you read. Use the template at assets/paper-summary-template.md.

See references/paper-reading.md for the full reading methodology and habit-building guidance.

Handoff to Idea Tournament or Planning

When you have a research direction but want to explore multiple concrete approaches, pass to idea-tournament for tree-structured generation and Elo ranking before planning.

When ideation is complete — you have a problem, a proposed solution approach, and supporting literature — pass these artifacts to paper-planning:

Artifact Source Step Used By
Research goal and scope Step 1 Story design (task definition)
Literature tree (novelty + challenge-insight) Step 2 Related work mapping, novelty claims
Problem statement and motivation Step 3 Introduction motivation paragraphs
Solution sketch and design rationale Step 4 Method section planning
Key failure cases to address Step 3 Experiment planning (stress tests)
Relevant prior work and their limitations Step 2 Baseline selection, comparison design

Reference Navigation

Topic Reference File When to Use
Literature tree construction literature-tree.md Mapping a research field
Problem selection problem-selection.md Evaluating whether a problem is worth solving
Solution design solution-design.md Designing a novel approach
Paper reading methodology paper-reading.md Reading papers effectively
Paper summary template paper-summary-template.md Writing structured paper notes

Expand your agent's capabilities with these related and highly-rated skills.

EvoScientist/EvoSkills

paper-writing

Guides writing academic papers section by section using an 11-step workflow with LaTeX templates and counterintuitive writing tactics. Covers Abstract, Introduction, Method, Experiments, Related Work, Conclusion, and Supplementary. Use when: user asks to write or draft a paper section, needs LaTeX templates, wants to improve academic writing quality, optimize novelty framing, or mentions 'write introduction', 'draft method', 'paper writing'. Do NOT use for pre-submission review (use paper-review), experiment execution (use experiment-pipeline), or paper planning/story design (use paper-planning).

141 17
Explore
EvoScientist/EvoSkills

evo-memory

Manages persistent research memory across ideation and experimentation cycles. Maintains two stores: Ideation Memory M_I (feasible/unsuccessful directions) and Experimentation Memory M_E (reusable strategies for data processing, model training, architecture, debugging). Three evolution mechanisms: IDE (after idea-tournament), IVE (after experiment failure — classifies failures as implementation vs fundamental), ESE (after experiment success — extracts reusable strategies). Use when: updating memory after completing idea tournaments or experiment pipelines, classifying why a method failed (implementation vs fundamental failure), starting a new research cycle needing prior knowledge, user mentions 'update memory', 'classify failure', 'what worked before', 'research history', 'evolution'. Do NOT use for running experiments (use experiment-pipeline), debugging experiment code (use experiment-craft), or generating ideas (use idea-tournament).

141 17
Explore
EvoScientist/EvoSkills

paper-navigator

End-to-end academic paper workflow: disambiguate queries, discover papers (search, citation traversal, recommendations, arXiv monitoring, trending, GitHub search), evaluate (TLDR, citations, code, SOTA), read with structured analysis (3-level strategy), and organize into literature maps or reports. Use when: finding papers, reading a paper, related work, literature survey, citation analysis, research trends, SOTA results, datasets, or literature reports. Do NOT use for writing a literature review section (use paper-writing), comparing research ideas (use idea-tournament), or planning paper structure (use paper-planning).

141 17
Explore
EvoScientist/EvoSkills

paper-review

Guides self-review of YOUR OWN academic paper before submission with adversarial stress-testing. Core method: 5-aspect checklist (contribution sufficiency, writing clarity, results quality, testing completeness, method design), counterintuitive protocol (reject-first simulation, delete unsupported claims, score trust, promote limitations, attack novelty), reverse-outlining, and figure/table quality checks. Use when: user wants to self-review or self-check their own paper draft before submission, stress-test their claims, prepare for reviewer criticism, or mentions 'self-review', 'check my draft', 'is my paper ready'. Do NOT use for writing a peer review of someone else's paper, and do NOT use after receiving actual reviews (use paper-rebuttal instead).

141 17
Explore
EvoScientist/EvoSkills

experiment-craft

Use this skill when the user wants to debug, diagnose, or systematically iterate on an experiment that already exists, or when they need a structured experiment log for tracking runs, hypotheses, failures, results, and next steps during active research. Apply it to underperforming methods, training that will not converge, regressions after a change, inconsistent results across datasets, aimless experimentation without progress, and questions like 'why doesn't this work?', 'no progress after many attempts', or 'how should I investigate this failure?'. Also use it for setting up practical experiment logging/record-keeping that supports debugging and iteration. Do not use it for designing a brand-new experiment pipeline or full experiment program (use experiment-pipeline), generating research ideas, fixing isolated coding/syntax errors, or writing retrospective summaries into research memory/notes/knowledge bases.

141 17
Explore
EvoScientist/EvoSkills

experiment-pipeline

Guides structured 4-stage experiment execution with attempt budgets and gate conditions: Stage 1 initial implementation (reproduce baseline), Stage 2 hyperparameter tuning, Stage 3 proposed method validation, Stage 4 ablation study. Integrates with evo-memory (load prior strategies, trigger IVE/ESE) and experiment-craft (5-step diagnostic on failure). Use when: user has a planned experiment, needs to reproduce baselines, organize experiment workflow, or systematically validate a method. Do NOT use for debugging a specific experiment failure (use experiment-craft) or designing which experiments to run (use paper-planning).

141 17
Explore

Didn't find tool you were looking for?

Be as detailed as possible for better results