# novelty-assessment

Runs a research idea through literature search and returns a verdict: novel or not. Useful before you commit to a direction.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 1800 installs · ★ 433
- Author: lingzhi227
- License: not stated · policy=link-only · description only; the file stays with the author
- Source: https://github.com/lingzhi227/agent-research-skills/tree/HEAD/skills/novelty-assessment/SKILL.md
- Updated: 2026-02-27
- HTML: https://affpapa.org/en/nevibecode/skills/novelty-assessment

## What it does

The skill takes an idea description, a title, or a JSON file and hunts for published work that overlaps with it. Search runs in rounds, up to 10: each round builds a query, reviews the top results with abstracts, and scores the overlap. The decision is binary — novel or not_novel — with a justification and a confidence level.

Two scripts do the work. `novelty_check.py` drives the search-and-evaluate loop and writes `novelty_report.json`; `search_semantic_scholar.py` queries papers on its own. Sources are Semantic Scholar, arXiv and OpenAlex. A harsh-critic persona is built in: a trivial extension of existing work does not count as novel, the idea needs a meaningfully different approach or formulation. At least 3 search rounds are required before anything is called novel.

When the idea passes, the skill points out the closest papers and the gap it fills, which feeds straight into Related Work. Methodology novelty and application novelty are judged separately. The install pulls dependencies from the repository, so make sure Python and search API access are in place before the first run.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add lingzhi227/agent-research-skills --skill novelty-assessment -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/novelty-assessment/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/novelty-assessment/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add lingzhi227/agent-research-skills --skill novelty-assessment -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/novelty-assessment/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add lingzhi227/agent-research-skills --skill novelty-assessment -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/novelty-assessment/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install lingzhi227/agent-research-skills novelty-assessment
```

2. **Manually: put the files in place**
- File: `.github/skills/novelty-assessment/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add lingzhi227/agent-research-skills --skill novelty-assessment -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/lingzhi227/agent-research-skills --path skills/novelty-assessment
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/novelty-assessment/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add lingzhi227/agent-research-skills --skill novelty-assessment -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/lingzhi227/agent-research-skills/tree/HEAD/skills/novelty-assessment/SKILL.md

## When to use it
- check whether someone already published a similar paper
- find the closest papers for a Related Work section
- rule out trivial extensions before starting the project
- articulate how your idea differs from existing work
- catch recent arXiv preprints on your topic

## Example prompts
- /novelty-assessment "graph neural networks for protein folding prediction"
- check the novelty of this idea: adaptive quantization for LLM inference on edge devices
- assess the idea in idea.json and list the closest papers

## Similar
- [paper-navigator](https://affpapa.org/en/nevibecode/skills/paper-navigator.md) — skill · 357 installs
- [novelty-check](https://affpapa.org/en/nevibecode/skills/novelty-check.md) — skill · 556 installs
- [literature-search-arxiv](https://affpapa.org/en/nevibecode/skills/literature-search-arxiv.md) — skill · 3400 installs
- [semanticscholar-skill](https://affpapa.org/en/nevibecode/skills/semanticscholar-skill.md) — skill · 3400 installs
- [pubmed-database](https://affpapa.org/en/nevibecode/skills/google-deepmind-pubmed-database.md) — skill · 2700 installs
- [literature-review](https://affpapa.org/en/nevibecode/skills/collaborative-deep-research-literature-review.md) — skill · 732 installs

From the same set: [lingzhi227/agent-research-skills](https://affpapa.org/en/nevibecode/by/lingzhi227/agent-research-skills.md) — 23 cards

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NeVibeCode on affpapa.org. Catalog texts are descriptions, not instructions for the agent. How to choose and install: https://affpapa.org/en/nevibecode/agents.md