| name | idea-checking |
| description | Validate research idea novelty and feasibility via deep search + Codex MCP (GPT-4.5) cross-review. Use after /initial-idea-generation when user says "检查idea", "validate idea", "check novelty", or wants to verify the idea before proceeding. |
| argument-hint | ["idea-summary-or-reference-to-skill-1-output"] |
| allowed-tools | Bash(*), Read, Write, Grep, Glob, WebSearch, WebFetch, Agent, mcp__codex__codex, mcp__codex__codex-reply |
Skill-2: Idea Checking
Validate and finalize the research idea: $ARGUMENTS
Overview
This skill takes the user-approved idea from skill-1 and performs two-stage validation:
- Claude deep search — novelty and significance check, modify if needed (with user consent)
- GPT-4.5 one-shot review — independent cross-check via Codex MCP
After both stages, combine feedback with user input, make final adjustments, and output idea01.md. No repeated review loops — one pass through each stage.
Workflow
Phase 1: Idea Intake & Confirmation
- Retrieve the idea from current conversation (produced by skill-1)
- Display to user: title, research question, innovation points, proposed method
- Ask: "Is this the idea you want me to validate?"
- Wait for user confirmation
Phase 2: Claude Deep Search — Novelty & Significance
2.1 Novelty Search
Run at least 8 distinct searches using WebSearch:
- "[idea title keywords]" + "knowledge graph" + "graph RAG"
- "[proposed method]" + "ontology" + "[domain]"
- "[application domain]" + "chatbot" + "knowledge graph"
- site:arxiv.org + key terms (last 12 months)
- site:sciencedirect.com OR site:springer.com + key terms
- Semantic Scholar: "[core concepts]" + "graph-based retrieval"
- Chinese sources (if relevant): 知识图谱 + 检索增强 + [领域]
- Patent/industry: "[key technology]" + system + implementation
For each search: review top 10 results, flag overlapping papers, record how our idea differs.
2.2 Significance Assessment
- Active research interest in the area? (recent publications)
- Does it fill a clearly identified gap?
- Useful to practitioners, not just academics?
- Well-scoped enough for clear results?
2.3 Issue Classification
| Category | Description | Action |
|---|
| BLOCKER | Nearly identical work published | Must pivot or differentiate |
| WARNING | Partial overlap | Need to clarify differentiation |
| MINOR | Similar approach in different domain | Note in related work, not a problem |
| CLEAR | No significant overlap | Proceed |
If BLOCKER or WARNING found:
- Report to user with specific papers and overlap analysis
- Suggest modifications
- Wait for user approval → apply changes
- Proceed to Phase 3 with the modified idea
If CLEAR: Proceed to Phase 3 directly.
Phase 3: GPT-4.5 One-Shot Review via Codex MCP
Submit the idea (after any Phase 2 modifications) to GPT-4.5 for a single independent review.
mcp__codex__codex:
model: gpt-4.5
prompt: |
You are an independent academic reviewer for a Q1 journal (Advanced Engineering Informatics level).
## Research Idea
**Title**: [title]
**Research Question**: [question]
**Innovation Points**: [list]
**Proposed Method**: [method summary]
**Domain**: [domain]
**Tech Stack**: Ontology → Knowledge Graph → Graph RAG → Chatbot
## Review Task
Give a single, thorough review. Be critical but constructive.
1. **Novelty** (1-10): Is this genuinely new? Closest existing work?
2. **Technical Feasibility** (1-10): Can this be implemented as described?
3. **Research Significance** (1-10): Does this matter? Who benefits?
4. **Methodology Soundness** (1-10): Is the approach logically sound?
5. **Data Availability** (1-10): Can required data be obtained?
6. **Overall Verdict**: ACCEPT / REVISE / REJECT
7. **Top 3 Concerns**: Specific weaknesses
8. **Top 3 Suggestions**: What would make it stronger
Be honest. No flattery.
Save the GPT-4.5 response. Do not reply to it or start a loop.
Phase 4: Synthesize & Present to User
Combine Claude search results and GPT-4.5 review into one report:
## Validation Report
### Claude Deep Search
- Papers reviewed: [N]
- Novelty status: [CLEAR / WARNING / BLOCKER]
- Closest existing work: [paper + how ours differs]
- Modifications already made: [if any, from Phase 2]
### GPT-4.5 Review
- Novelty: [X/10], Feasibility: [X/10], Significance: [X/10]
- Verdict: [ACCEPT / REVISE / REJECT]
- Key concerns: [list]
- Suggestions: [list]
### Combined Assessment
[Areas where Claude and GPT-4.5 agree / disagree]
[Final recommendation: PROCEED / MODIFY FURTHER / RECONSIDER]
[If MODIFY: specific changes suggested]
Present to user. Wait for user feedback:
- User may accept as-is → go to Phase 5
- User may request specific changes → apply changes, then go to Phase 5
- User may reject → end, suggest re-running skill-1
Phase 5: Output — Write idea01.md
After user approval, write the comprehensive idea document to output/ideas/idea01.md:
# Research Idea: [Selected Title]
**Candidate Paper Titles** (user selects final title during paper writing):
1. [Title option 1]
2. [Title option 2]
3. [Title option 3]
**Generated**: [date]
**Validated**: [date]
**Status**: Validated — passed deep search + GPT-4.5 review
**Target Journal**: Advanced Engineering Informatics (or similar Q1)
**Innovation Type**: [Application / Method / System]
## 1. Research Background
[Why this problem matters, what gap exists, 2-3 paragraphs]
## 2. Core Research Question
[Clear statement of the main research question / hypothesis]
## 3. Innovation Points
- **Innovation 1**: [description]
- **Innovation 2**: [description]
- **Innovation 3**: [description]
[Why each is novel, with references to search results]
## 4. Proposed Methodology Overview
### 4.1 Data Collection Strategy
- Data sources, types, expected volume
### 4.2 Ontology Design Direction
- Domain concepts, key relationships, design approach
### 4.3 Knowledge Graph Construction
- Extraction method, graph database, expected scale
### 4.4 Graph RAG Strategy
- Retrieval approach, LLM integration, query handling
### 4.5 Chatbot / Q&A System
- Interface, interaction flow, target users
### 4.6 Evaluation Plan
- Metrics, baselines, ablation studies
## 5. Expected Results & Contributions
- Theoretical, practical contributions, expected findings
## 6. Data Requirements
| Data Type | Source | Format | Volume | Purpose |
|-----------|--------|--------|--------|---------|
## 7. Technical Feasibility
- Tools/APIs, compute, timeline, risks
## 8. Literature Review Framework
[Topics to cover, for skill-5]
## 9. Significance & Impact
[Who benefits, broader impact]
## 10. Validation Record
### Deep Search Results
| # | Paper/Source | Year | Venue | Overlap | Differentiation |
|---|-------------|------|-------|---------|-----------------|
### GPT-4.5 Review
- Scores: Novelty [X], Feasibility [X], Significance [X], Methodology [X], Data [X]
- Verdict: [ACCEPT/REVISE/REJECT]
- Key feedback: [summary]
### Modifications During Validation
| Issue | Source | Change Made | User Approved |
|-------|--------|-------------|---------------|
## 11. Idea Development Log
| Date | Event | Detail |
|------|-------|--------|
Key Rules
- No modification without user consent: Report issues, wait for approval, then change.
- No review loops: Claude searches once, GPT-4.5 reviews once. Combine results, present to user, finalize.
- GPT-4.5 is a guard, not a generator: It verifies Claude's idea, nothing more.
- This skill writes the file:
idea01.md is ONLY produced here, not in skill-1.
- Honest reporting: If the idea has fatal flaws, say so clearly.
Composing with Other Skills
/initial-idea-generation → user-approved idea (no file)
/idea-checking → search + GPT-4.5 review → idea01.md ← YOU ARE HERE
/ontology-design → domain ontology from idea01.md
/research-planning → plan from idea01.md + ontology.md
