Novelty Check

VerifiedSafe

Systematically verify whether a research idea is novel against recent literature using web search and a secondary AI agent.

Sby Skills Guide Bot
Data & AIIntermediate
7/22/2026
Claude CodeCodex
#novelty-check#literature-review#prior-art#research#arxiv

Recommended for

Automated summary

This skill checks whether a research idea has already appeared in the literature by extracting its core technical claims, searching arXiv, Google Scholar and Semantic Scholar, then producing a structured novelty report with a score and a recommendation.

Strengths

  • Breaks the idea into 3-5 separate technical claims and rates novelty for each one individually
  • Queries multiple sources with at least three phrasings per claim, filtered to 2024-2026 and with an explicit check of the last six months on arXiv
  • Adds cross-model verification through a secondary gpt-5.4 agent via spawn_agent to challenge the findings
  • Delivers an actionable artifact: closest-prior-work table, X/10 score, PROCEED / CAUTION / ABANDON verdict, and positioning advice

Limitations

  • Quality depends entirely on WebSearch and WebFetch results; paywalled databases are not covered
  • The list of venues (ICLR, NeurIPS, ICML) is hardcoded and needs updating each conference cycle
  • Requires a configured secondary Codex agent running an OpenAI model; otherwise the cross-verification phase is skipped
  • The novelty score is still a model judgment, not documented proof of prior art
When to use it

Use it before sinking weeks into implementing a research method, to surface the prior work a reviewer would cite against you.

When not to use it

Don't treat it as a replacement for an exhaustive literature review or for patent/legal prior-art searches, and avoid it when no web access or secondary agent is available.

Security analysis

Safe
Quality score88/100

The skill instructs literature search and cross-model verification using WebSearch, WebFetch, and a secondary agent. It does not perform destructive, exfiltrating, or obfuscated actions. No risky shell commands or token exfiltration are present. The only minor operational note is that referenced tools are not declared in allowed-tools, but this is not a security risk.

No concerns found

How this analysis is made

Examples

Check a new method idea
Novelty check: I want to combine a diffusion prior with sparse-view 3D reconstruction and add a test-time consistency loss. Has anyone done this already?
Chinese trigger phrase
查新:我的方法是在 LLM agent 上用分层记忆压缩长对话,同时用一个 reward model 做检索路由,有没有人做过?
Verify experimental setting
check novelty of this experimental setting — evaluating reasoning models on cross-lingual math benchmarks with a translated chain-of-thought protocol. Is the setting itself novel or just the finding?

name: "novelty-check" description: "Verify research idea novelty against recent literature. Use when user says "\u67e5\u65b0", "novelty check", "\u6709\u6ca1\u6709\u4eba\u505a\u8fc7", "check novelty", or wants to verify a research idea is novel before implementing."

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 a secondary Codex agent. 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 spawn_agent (spawn_agent) with xhigh reasoning:

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:

## 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

From the file to a first result

The download contains exactly the content displayed on this page. This copy may differ from the latest version in the source repository.

View the source and supporting files

This download contains SKILL.md only. Any scripts, references, templates and dependencies are not included. Get the required files from the source, preserving their directory structure, before continuing.

1. Download the file

Download SKILL.md

From the root of a test project, save the file as .skill-downloads/novelty-check-mrwakcus/SKILL.md, or use the command below. This folder is for inspecting the skill before installation.

Command for macOS/Linux or WSL: requires a POSIX shell and curl. On Windows without WSL, use the download button and create the folder manually.

mkdir -p '.skill-downloads/novelty-check-mrwakcus' && curl --fail --show-error --location 'https://skills-guides.com/api/skills/novelty-check-mrwakcus/download' --output '.skill-downloads/novelty-check-mrwakcus/SKILL.md.part' && mv '.skill-downloads/novelty-check-mrwakcus/SKILL.md.part' '.skill-downloads/novelty-check-mrwakcus/SKILL.md'

2. Check prerequisites

Read SKILL.md before using it. If it references scripts or external services, inspect them and prepare the required access in your test environment.

No recognized prerequisites section in this file. This does not mean it is self-contained: libraries, tools and access requirements may be mentioned elsewhere in the content or source repository.

The platforms on this page are catalog indications. The paths below follow tool documentation; they do not prove this skill has been run in those tools. No minimum tool version is confirmed for this listing.

3. Load the skill

After inspection, copy the complete folder into your project using one of the commands below, then open a new tool session. The command stops if a folder with the same name already exists: compare the files before replacing it.

Claude Code
test -f '.skill-downloads/novelty-check-mrwakcus/SKILL.md' && test -s '.skill-downloads/novelty-check-mrwakcus/SKILL.md' && mkdir -p '.claude/skills' && test ! -e '.claude/skills/novelty-check' && cp -R '.skill-downloads/novelty-check-mrwakcus' '.claude/skills/novelty-check'

Codex
test -f '.skill-downloads/novelty-check-mrwakcus/SKILL.md' && test -s '.skill-downloads/novelty-check-mrwakcus/SKILL.md' && mkdir -p '.agents/skills' && test ! -e '.agents/skills/novelty-check' && cp -R '.skill-downloads/novelty-check-mrwakcus' '.agents/skills/novelty-check'

OpenSkills

OpenSkills must already be installed. The local install/read procedure is checked with OpenSkills 1.5.0, which requires Node.js ≥ 20.6.0. Catalog slugs are not resolved automatically.

Official OpenSkills installation
openskills install './.skill-downloads/novelty-check-mrwakcus'

openskills read 'novelty-check-mrwakcus'

Reading should display the installed file content and its base directory. It does not run the skill or install its dependencies.

For an agent that reads AGENTS.md, then sync the index. This command changes AGENTS.md: review the diff before using it.

openskills sync

Manual method or another tool: attach SKILL.md to a conversation, or open it in an agent that can read files. Include any required supporting resources. No universal folder is recognized by every tool.

4. Try a first task

Use a short, synthetic input: an API endpoint, a small document or an interface brief. In a new conversation, attach the file or give the agent its path, then adapt this request:

Read .skill-downloads/novelty-check-mrwakcus/SKILL.md and apply its instructions to this example: [describe a test input]. Identify any missing files, dependencies or access. Produce the result requested by the skill without inventing data or running unreviewed scripts.

Expected result: output matching the skill instructions, or a precise list of missing prerequisites. A read confirmation alone does not validate a first use. If an external resource is unavailable, that path remains untested.

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