---
name: Novelty Check
slug: novelty-check
category: AI Engineering
description: Novelty Check verifies whether a proposed research method or idea has already appeared in recent literature. Use it before implementation when you need a blunt assessment of overlap and likely prior work.
github: "https://github.com/OpenLAIR/dr-claw/tree/main/skills/aris-novelty-check"
language: JavaScript
stars: 1047
forks: 116
install: "npx degit https://github.com/OpenLAIR/dr-claw/tree/main/skills/aris-novelty-check ~/.claude/skills/aris-novelty-check"
installs_to: ~/.claude/skills/aris-novelty-check
source_path: skills/aris-novelty-check/SKILL.md
collection_size: 25
category_size: 2451
collection_url: "https://dirskills.com/collections/OpenLAIR/dr-claw"
added: 2026-08-21T05:14:02.977Z
last_synced: 2026-08-21T05:14:02.977Z
canonical_url: "https://dirskills.com/skills/novelty-check"
---

# Novelty Check

Novelty Check verifies whether a proposed research method or idea has already appeared in recent literature. Use it before implementation when you need a blunt assessment of overlap and likely prior work.

**Install:**

```bash
npx degit https://github.com/OpenLAIR/dr-claw/tree/main/skills/aris-novelty-check ~/.claude/skills/aris-novelty-check
```

## README

# Novelty Check Skill

Check whether a proposed method/idea has already been done in the literature: **$ARGUMENTS**

## Constants

- REVIEWER_MODEL = `gpt-5.4` — Model used via Codex MCP. Must be an OpenAI model (e.g., `gpt-5.4`, `o3`, `gpt-4o`)

## Instructions

Given a method description, systematically verify its novelty:

### Phase A: Extract Key Claims
1. Read the user's method description
2. Identify 3-5 core technical claims that would need to be novel:
   - What is the method?
   - What problem does it solve?
   - What is the mechanism?
   - What makes it different from obvious baselines?

### Phase B: Multi-Source Literature Search
For EACH core claim, search using ALL available sources:

1. **Web Search** (via `WebSearch`):
   - Search arXiv, Google Scholar, Semantic Scholar
   - Use specific technical terms from the claim
   - Try at least 3 different query formulations per claim
   - Include year filters for 2024-2026

2. **Known paper databases**: Check against:
   - ICLR 2025/2026, NeurIPS 2025, ICML 2025/2026
   - Recent arXiv preprints (2025-2026)

3. **Read abstracts**: For each potentially overlapping paper, WebFetch its abstract and related work section

### Phase C: Cross-Model Verification
Call REVIEWER_MODEL via Codex MCP (`mcp__codex__codex`) with xhigh reasoning:
```
config: {"model_reasoning_effort": "xhigh"}
```
Prompt should include:
- The proposed method description
- All papers found in Phase B
- Ask: "Is this method novel? What is the closest prior work? What is the delta?"

### Phase D: Novelty Report
Output a structured report:

```markdown
## Novelty Check Report

### Proposed Method
[1-2 sentence description]

### Core Claims
1. [Claim 1] — Novelty: HIGH/MEDIUM/LOW — Closest: [paper]
2. [Claim 2] — Novelty: HIGH/MEDIUM/LOW — Closest: [paper]
...

### Closest Prior Work
| Paper | Year | Venue | Overlap | Key Difference |
|-------|------|-------|---------|----------------|

### Overall Novelty Assessment
- Score: X/10
- Recommendation: PROCEED / PROCEED WITH CAUTION / ABANDON
- Key differentiator: [what makes this unique, if anything]
- Risk: [what a reviewer would cite as prior work]

### Suggested Positioning
[How to frame the contribution to maximize novelty perception]
```

### Important Rules
- Be BRUTALLY honest — false novelty claims waste months of research time
- "Applying X to Y" is NOT novel unless the application reveals surprising insights
- Check both the method AND the experimental setting for novelty
- If the method is not novel but the FINDING would be, say so explicitly
- Always check the most recent 6 months of arXiv — the field moves fast