| name | research-project-coordination |
| description | Manage large-scale research projects requiring multiple phases of discovery, analysis, and synthesis. Use when user is working on survey papers, thesis chapters, or comprehensive research projects. |
| tools | ["create_research_question","run_discovery_for_question","list_research_questions","list_articles","search_articles","collection_stats","compare_articles","answer_research_question","explore_citation_network"] |
Research Project Coordination
Coordinate multi-phase research projects that require systematic discovery, collection building, and synthesis over time.
Tools to Use
This skill uses tools from multiple categories:
Discovery Phase:
create_research_question - Create search queries
run_discovery_for_question - Execute searches
list_available_sources - Source selection
Collection Phase:
list_articles - Browse papers
search_articles - Filter collection
collection_stats - Track progress
Analysis Phase (delegate to Research Analyst):
compare_articles - Cross-paper analysis
answer_research_question - Comprehensive synthesis with citations
explore_citation_network - Citation mapping
Management:
list_skills - Load additional skills as needed
load_skill - Get specialized guidance
Project Types
Survey Paper
Multi-topic comprehensive literature review covering an entire field.
Thesis Chapter
Focused deep dive into a specific research question with background.
Grant Proposal Background
Evidence gathering to support research direction claims.
Competitive Analysis
Systematic comparison of approaches/methods in a space.
Project Phases
Phase 1: Scoping & Planning
1. Define project scope
- Main research question
- Sub-topics to cover
- Expected output (survey, thesis, etc.)
- Timeline constraints
2. Create project structure
Project: [name]
├── Topic 1: [subtopic]
│ └── Queries: [list]
├── Topic 2: [subtopic]
│ └── Queries: [list]
└── Topic N: [subtopic]
└── Queries: [list]
3. Set collection targets
- Papers per topic: [count]
- Quality threshold: [value]
- Time range: [years]
Phase 2: Systematic Discovery
For each sub-topic:
1. Create targeted query
create_research_question(
title="[topic] for [project name]",
keywords=["specific", "terms"],
sources=["appropriate", "sources"],
max_papers=50
)
2. Execute discovery
run_discovery_for_question(question_id="...")
3. Track progress
collection_stats()
4. Adjust if needed
- Too few results → broaden keywords
- Wrong focus → refine terms
Phase 3: Collection Curation
1. Review discovered papers
list_articles(limit=100, sort_by="relevance")
2. Identify key papers per topic
search_articles(query="[topic keyword]", limit=20)
3. Check coverage gaps
- Missing seminal papers?
- Recent work included?
- All approaches represented?
4. Fill gaps with targeted searches
Phase 4: Analysis & Synthesis
Delegate to Research Analyst:
send_message_to_agent(
agent_name="Research Analyst",
message="For the [project name] project, please:
1. Analyze papers in [topic] category
2. Generate synthesis for [section name]
3. Identify key themes and research gaps
Papers to analyze: [list of IDs]
Output format: [structured summary / comparison table / narrative]"
)
Phase 5: Integration
Combine analyses into final output:
1. Gather section summaries from Research Analyst
2. Identify cross-cutting themes
3. Highlight research gaps
4. Suggest future directions
Progress Tracking
Maintain project status in conversation:
## Project: [Name]
Status: [Phase X of 5]
Started: [date]
### Topics Progress:
| Topic | Queries | Papers | Analyzed | Status |
|-------|---------|--------|----------|--------|
| Topic 1 | 2 | 45 | 20 | ✓ Complete |
| Topic 2 | 3 | 62 | 0 | In Progress |
| Topic 3 | 1 | 0 | 0 | Pending |
### Next Steps:
1. [immediate action]
2. [upcoming action]
Workflow Examples
Example 1: Survey Paper on LLM Efficiency
User: "I'm writing a survey paper on efficient large language models"
Phase 1: Scoping
"Let's plan your survey. I'll break this into sub-topics:
1. **Architectural Efficiency**
- Sparse attention mechanisms
- State space models
- Mixture of experts
2. **Training Efficiency**
- Parameter-efficient fine-tuning
- Distillation methods
- Curriculum learning
3. **Inference Optimization**
- Quantization
- Pruning
- Speculative decoding
4. **Hardware-Aware Design**
- Memory optimization
- Hardware co-design
For each topic, I'll create discovery queries targeting ~30-50 papers.
Total target: ~150-200 papers across topics.
Shall I proceed with this structure?"
Phase 2: Discovery (for each topic)
create_research_question(
title="Sparse Attention for LLM Efficiency Survey",
keywords=["sparse attention", "efficient transformer", "linear attention"],
sources=["arxiv", "semantic_scholar"],
max_papers=50
)
run_discovery_for_question(...)
Phase 3: Track progress
"Discovery progress update:
| Topic | Papers Found | Status |
|-------|--------------|--------|
| Sparse Attention | 47 | ✓ |
| State Space Models | 38 | ✓ |
| MoE | 52 | ✓ |
| PEFT | 61 | In Progress |
| ... | ... | ... |
Total: 198 papers. Ready to begin analysis?"
Phase 4: Analysis (delegated)
send_message_to_agent(
agent_name="Research Analyst",
message="Survey analysis request for LLM Efficiency Survey:
Section: Sparse Attention Mechanisms
Papers: [list of 47 paper IDs]
Please provide:
1. Taxonomy of approaches
2. Comparative analysis table
3. Evolution timeline (2020-2024)
4. Key research gaps
5. Section summary (~500 words)"
)
Example 2: Thesis Background Chapter
User: "Help me build the background chapter for my thesis on multimodal learning"
Phase 1: Scoping
"For a thesis background, we need:
1. **Foundational Work** (pre-2020)
- Early multimodal approaches
- Key theoretical frameworks
2. **Core Methods** (2020-2023)
- Vision-language models
- Audio-visual learning
- Cross-modal attention
3. **Recent Advances** (2023-present)
- Unified architectures
- Scaling studies
- Emergent capabilities
4. **Your Specific Focus Area**
- [user's thesis topic]
I'll prioritize seminal papers and highly-cited work.
Target: ~80-100 papers total."
Phase 2-4: [Execute systematically]
Phase 5: Integration
"Background chapter structure ready:
## 2. Background and Related Work
### 2.1 Foundations of Multimodal Learning
[synthesis from foundational papers]
### 2.2 Vision-Language Models
[synthesis from VLM papers]
### 2.3 Cross-Modal Attention Mechanisms
[synthesis from attention papers]
### 2.4 Recent Advances and Open Challenges
[synthesis from recent papers]
### 2.5 Summary and Research Gap
[leading to your contribution]
Each section has been drafted with proper citations.
Would you like me to refine any section?"
Project Templates
Survey Paper Template
Sections: 6-8 topic areas
Papers per section: 20-40
Total papers: 150-300
Timeline: 4-8 weeks
Analysis depth: Comprehensive taxonomy + comparison
Thesis Background Template
Sections: 4-5 areas
Papers per section: 15-25
Total papers: 60-100
Timeline: 2-4 weeks
Analysis depth: Historical context + state of art
Grant Proposal Template
Sections: 2-3 key areas
Papers per section: 10-15
Total papers: 30-50
Timeline: 1-2 weeks
Analysis depth: Evidence for claims + gap identification
Coordination Notes
- Checkpoints: Review with user after each phase
- Iteration: Expect 2-3 refinement cycles
- Delegation: Use Research Analyst for deep analysis
- Documentation: Keep project state updated
- Flexibility: Adapt structure based on findings