novelty-assessment

Name: novelty-assessment
Author: lingzhi227

Assess research idea novelty through systematic literature search. Multi-round search-evaluate loops with harsh critic persona. Binary novel/not-novel decision…

INSTALLATION

npx skills add https://github.com/lingzhi227/agent-research-skills --skill novelty-assessment

Run in your project or agent environment. Adjust flags if your CLI version differs.

SKILL.md

Novelty Assessment

Rigorously assess whether a research idea is novel through systematic literature search.

Input

$0 — Research idea description, title, or JSON file

Scripts

Automated novelty check

python ~/.claude/skills/idea-generation/scripts/novelty_check.py \

  --idea "Your research idea description" \

  --max-rounds 10 --output novelty_report.json

Literature search

python ~/.claude/skills/deep-research/scripts/search_semantic_scholar.py \

  --query "relevant search query" --max-results 10

References

Assessment prompts and criteria: ~/.claude/skills/novelty-assessment/references/assessment-prompts.md

Workflow

Step 1: Understand the Idea

Identify the core contribution

List the key technical components

Determine the research area and subfield

Step 2: Multi-Round Literature Search (up to 10 rounds)

For each round:

Generate a targeted search query

Search Semantic Scholar / arXiv / OpenAlex

Review top-10 results with abstracts

Assess overlap with the idea

Decide: need more searching, or ready to decide

Step 3: Make Decision

Novel: After sufficient searching, no paper significantly overlaps

Not Novel: Found a paper that significantly overlaps

Step 4: Position the Idea

If novel, identify:

Most similar existing papers (for Related Work)

How the idea differs from each

The specific gap this idea fills

Harsh Critic Persona

Be a harsh critic for novelty. Ensure there is a sufficient contribution

for a new conference or workshop paper. A trivial extension of existing

work is NOT novel. The idea must offer a meaningfully different approach,

formulation, or insight.

Output Format

{

  "decision": "novel" | "not_novel",

  "confidence": "high" | "medium" | "low",

  "justification": "After searching X rounds...",

  "most_similar_papers": [

    {"title": "...", "year": 2024, "overlap": "..."}

  ],

  "differentiation": "Our idea differs because..."

}

Rules

Minimum 3 search rounds before declaring novel

Try to recall exact paper names for targeted queries

A paper idea is NOT novel if it's a trivial extension

Consider both methodology novelty AND application novelty

Check for concurrent/recent arXiv submissions

Related Skills

Upstream: literature-search, deep-research

Downstream: idea-generation, research-planning

See also: related-work-writing