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Skill

/novelty-assessment

Assess research idea novelty through systematic literature search. Multi-round search-evaluate loops with harsh critic persona. Binary novel/not-novel decision with justification. Use before committing to a research direction.

From plugin
agent-research-skills
26531 skills1 command
Install
$ npx -y skills add lingzhi227/agent-research-skills --skill novelty-assessment --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/novelty-assessment

Context preview

The summary Claude sees to decide when to auto-load this skill.

Assess research idea novelty through systematic literature search. Multi-round search-evaluate loops with harsh critic persona. Binary novel/not-novel decision with justification. Use before committing to a research direction.

SKILL.md

novelty-assessment.SKILL.md
name: novelty-assessment
description: Assess research idea novelty through systematic literature search. Multi-round search-evaluate loops with harsh critic persona. Binary novel/not-novel decision with justification. Use before committing to a research direction.
argument-hint: [idea]

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: 1. Generate a targeted search query 2. Search Semantic Scholar / arXiv / OpenAlex 3. Review top-10 results with abstracts 4. Assess overlap with the idea 5. 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](../literature-search/), [deep-research](../deep-research/)
  • Downstream: [idea-generation](../idea-generation/), [research-planning](../research-planning/)
  • See also: [related-work-writing](../related-work-writing/)
Read more
Ships withagent-research-skills

31 skills for Claude Code covering the full academic research paper lifecycle — from literature search to slide generation — plus GitHub repository analysis for research topics. Extracted from 17 GitHub repos studying LLM-agent-driven research automation.

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Repo: lingzhi227/agent-research-skills

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