This runs a systematic literature search loop to figure out if your research idea already exists. It does up to 10 rounds of searches across Semantic Scholar and arXiv, checking each batch of papers for overlap. The harsh critic persona is useful here: it won't let you ship a trivial extension as novel work. You get a binary novel or not novel decision with confidence level and specific papers that come close. Minimum three search rounds before it'll declare something novel. Best used before you commit weeks to a direction, and the structured JSON output feeds nicely into related work sections if you proceed.

skills.sh installs
1.9K
GitHub stars
459
last updated
Aug 21, 2026

Install

$ npx -y skills add lingzhi227/agent-research-skills --skill novelty-assessment --agent claude-code

Installs into .claude/skills of the current project.

Files

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

Sponsors

Details

Repository
github.com/lingzhi227/agent-research-skills
Categories
AI & Agent Building, Data Science & ML, Productivity & Planning
First seen
Jun 3, 2026

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