skills/42-wanshuiyin-ARIS/skills/skills-codex-gemini-review/novelty-check/SKILL.md
Verify research idea novelty against recent literature. Use when user says "查新", "novelty check", "有没有人做过", "check novelty", or wants to verify a research idea is novel before implementing.
npx skillsauth add brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research novelty-checkInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Override for Codex users who want Gemini, not a second Codex agent, to act as the reviewer. Install this package after
skills/skills-codex/*.
Check whether a proposed method/idea has already been done in the literature: $ARGUMENTS
gemini-review — Gemini reviewer invoked through the local gemini-review MCP bridge. Set GEMINI_REVIEW_MODEL if you need a specific Gemini model override.Given a method description, systematically verify its novelty:
For EACH core claim, search using ALL available sources:
Web Search (via WebSearch):
Known paper databases: Check against:
Read abstracts: For each potentially overlapping paper, WebFetch its abstract and related work section
Call REVIEWER_MODEL via mcp__gemini-review__review_start with high-rigor review:
mcp__gemini-review__review_start:
prompt: |
[Full novelty briefing + prior work list + specific novelty questions]
After this start call, immediately save the returned jobId and poll mcp__gemini-review__review_status with a bounded waitSeconds until done=true. Treat the completed status payload's response as the reviewer output, and save the completed threadId for any follow-up round.
Prompt should include:
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]
tools
Autonomous multi-round research review loop using MiniMax API. Use when you want to use MiniMax instead of Codex MCP for external review. Trigger with "auto review loop minimax" or "minimax review".
tools
Autonomous research review loop using any OpenAI-compatible LLM API. Configure via llm-chat MCP server or environment variables. Trigger with "auto review loop llm" or "llm review".
tools
Autonomous multi-round research review loop using MiniMax API. Use when you want to use MiniMax instead of Codex MCP for external review. Trigger with "auto review loop minimax" or "minimax review".
tools
Autonomous research review loop using any OpenAI-compatible LLM API. Configure via llm-chat MCP server or environment variables. Trigger with "auto review loop llm" or "llm review".