research-discovery-execution

name	research-discovery-execution
description	Execute and monitor discovery sessions for finding research papers across academic sources. Use when running discovery searches.

Research Discovery Execution

Execute discovery searches systematically and monitor their progress to find relevant research papers.

Quick Start: Running Discovery

Most common use: User needs to find papers on a specific topic from academic sources.

Standard Execution

User request: "Find papers on quantum error correction from 2024"

Step 1: Verify research question exists
- Use list_research_questions
- If doesn't exist, tell orchestrator to create one first

Step 2: Run discovery
- Use run_discovery_for_question
- Specify question ID or name
- Set parameters (date range, sources)

Step 3: Monitor progress
- Update workflow_state with status
- Check for errors or timeouts
- Provide progress updates

Step 4: Return results
- Count of papers found per source
- Summary of top papers
- Quality metrics (relevance scores)

---

Discovery Workflow

Phase 1: Validation

Before running discovery, validate:

1. Research question exists
2. Sources are available
3. Parameters are valid
4. No duplicate recent searches

Check existing research questions:
questions = list_research_questions()

If question not found:
"The research question hasn't been created yet. The orchestrator
should create it first using the research-question-creation skill."

If question exists but recently run:
"This discovery was run 2 hours ago. Found 45 papers.
Do you want to run again or use existing results?"

Phase 2: Execution

Run discovery with proper parameters:

run_discovery_for_question(
    question_id="...",
    force_refresh=False,  # Set to True to ignore cache
    max_results=100,      # Limit per source
    min_relevance=0.7     # Quality threshold
)

Sources checked (in order):

1. arXiv (fast, high quality)
2. Semantic Scholar (comprehensive)
3. PubMed (biomedical focus)
4. CrossRef (broad coverage)
5. bioRxiv (preprints)

Phase 3: Monitoring

Update workflow_state during execution:

Initial:
"Discovery Status: Starting
Sources: arXiv, Semantic Scholar, PubMed
Expected time: 1-2 minutes"

During:
"Discovery Status: In Progress
arXiv: 23 papers found (complete)
Semantic Scholar: 15 papers found (in progress)
PubMed: pending
Time elapsed: 45 seconds"

Complete:
"Discovery Status: Complete
Total papers: 52
Sources: arXiv (23), Semantic Scholar (18), PubMed (11)
Duration: 118 seconds
Quality: 38 papers above relevance threshold"

Phase 4: Results Processing

Analyze and summarize results:

For each source:
- Count of papers found
- Quality distribution (high/medium/low relevance)
- Date range covered
- Top papers by relevance score

Overall:
- Total unique papers (deduplicating across sources)
- Papers meeting quality threshold
- Recommended next steps

---

Error Handling

Common Errors and Solutions

Error: "Source timeout"

Problem: arXiv taking >60 seconds
Solution: Continue with other sources
Action: "arXiv timed out, but found 33 papers from Semantic Scholar
         and PubMed. Do you want to retry arXiv or proceed with these?"

Error: "No papers found"

Problem: Search too narrow or no matching papers
Solution: Suggest broadening search
Action: "No papers found matching these criteria. Suggestions:
         - Broaden date range (try last 2 years instead of 6 months)
         - Add related keywords
         - Try different sources"

Error: "Rate limit exceeded"

Problem: Too many requests to source
Solution: Wait and retry, or skip source
Action: "Hit rate limit on Semantic Scholar. Waiting 30 seconds...
         Meanwhile, found 20 papers from arXiv."

Error: "Invalid research question"

Problem: Research question malformed or missing
Solution: Tell orchestrator to fix/create question
Action: "Research question needs to be created or fixed. Delegating
         back to orchestrator..."

---

Quality Thresholds

Relevance Scoring

Papers are scored 0.0-1.0 based on:

• Title/abstract keyword matches (40%)
• Semantic similarity (30%)
• Citation count (20%)
• Publication venue (10%)

Thresholds:

• High quality: >0.8 - Highly relevant, well-cited
• Medium quality: 0.6-0.8 - Relevant, decent citations
• Low quality: <0.6 - Tangentially related

Filtering Strategy

Default: Return all papers >0.6 relevance
Strict mode: Only >0.8 relevance
Exploratory mode: All papers >0.4 relevance

Example:
Found 80 papers total:
- 25 high quality (>0.8)
- 35 medium quality (0.6-0.8)
- 20 low quality (<0.6)

Recommended: Present high + medium (60 papers)

---

Source-Specific Notes

arXiv

• Best for: Computer Science, Physics, Math
• Speed: Fast (10-30 seconds)
• Quality: High (peer-reviewed preprints)
• Limitation: No biomedical papers

Semantic Scholar

• Best for: Comprehensive coverage across fields
• Speed: Medium (30-60 seconds)
• Quality: Variable (includes preprints and journals)
• Strength: Great citation data

PubMed

• Best for: Biomedical and life sciences
• Speed: Medium (20-40 seconds)
• Quality: High (peer-reviewed journals)
• Limitation: Only biomedical topics

CrossRef

• Best for: DOI-based lookups, broad coverage
• Speed: Slow (60-120 seconds)
• Quality: Variable
• Use case: Fallback for other sources

bioRxiv

• Best for: Latest biomedical preprints
• Speed: Fast (15-30 seconds)
• Quality: Medium (not peer-reviewed)
• Strength: Cutting-edge research

---

Advanced Patterns

Pattern A: Incremental Discovery

For large searches, run in batches:

Batch 1: Last 6 months (quick)
→ Review results
→ If insufficient, expand to 1 year
Batch 2: 6-12 months ago
→ Merge with Batch 1
→ If still insufficient, expand to 2 years

Pattern B: Multi-Phase Discovery

For complex topics:

Phase 1: Core keywords (narrow)
→ Get foundational papers

Phase 2: Related keywords (broad)
→ Find connections and context

Phase 3: Citation expansion
→ Papers cited by Phase 1 papers

Pattern C: Source Prioritization

Based on topic:

Computer Science topic:
Priority: arXiv > Semantic Scholar > CrossRef

Biomedical topic:
Priority: PubMed > bioRxiv > Semantic Scholar

Interdisciplinary:
Priority: Semantic Scholar > arXiv > PubMed

---

Performance Optimization

Parallel Source Queries

Sources can be queried in parallel:

Start all sources simultaneously:
- arXiv query (async)
- Semantic Scholar query (async)
- PubMed query (async)

Return results as they complete:
"arXiv: 23 papers found (15 seconds)"
"Semantic Scholar: still searching..."
"PubMed: 11 papers found (22 seconds)"

Caching Strategy

Cache results for 24 hours:
- Same research question
- Same parameters
- Within 24 hours

Skip cache if:
- force_refresh=True
- User explicitly asks for fresh search
- Important new papers expected (conference just happened)

---

Result Formatting

Always provide structured results:

=== Discovery Results ===

**Summary:**
- Total papers: 52
- High quality: 25 papers
- Date range: Jan 2024 - Jan 2025
- Duration: 118 seconds

**By Source:**
1. arXiv: 23 papers (10-30s search time)
2. Semantic Scholar: 18 papers (45s search time)
3. PubMed: 11 papers (25s search time)

**Top 5 Papers:**
1. "Quantum Error Correction with..." (relevance: 0.95, 150 cites)
2. "Surface Codes for Fault-Tolerant..." (relevance: 0.92, 120 cites)
3. ...

**Quality Distribution:**
- High (>0.8): 25 papers
- Medium (0.6-0.8): 20 papers
- Below threshold (<0.6): 7 papers (filtered out)

**Next Steps:**
Would you like me to:
- Download PDFs for high-quality papers?
- Run citation analysis?
- Create a reading list?

---

Integration with Workflow State

Always update workflow_state during discovery:

Start:
workflow_state: "Discovery started for quantum error correction"

Progress:
workflow_state: "Discovery 50% complete, 30 papers found so far"

Complete:
workflow_state: "Discovery complete: 52 papers found in 118 seconds"

Update active_papers memory:
"Papers pending download: [list of paper IDs]"

Update research_context:
"Current research: quantum error correction
Latest discovery: Jan 2025, 52 papers"

---

Quick Reference

Discovery Checklist

• Research question exists
• Sources are valid for topic
• Parameters set (date range, max results)
• workflow_state updated (starting)
• Run discovery
• Monitor progress
• Handle errors gracefully
• workflow_state updated (progress)
• Process and filter results
• Update memory blocks
• workflow_state updated (complete)
• Format and return results

Common Parameters

Standard search:
- Date range: Last 2 years
- Max results: 100 per source
- Min relevance: 0.7

Quick search:
- Date range: Last 6 months
- Max results: 50 per source
- Min relevance: 0.8

Comprehensive search:
- Date range: Last 5 years
- Max results: 200 per source
- Min relevance: 0.6

---

Summary

Your job as Discovery Scout:

1. Validate research question exists
2. Run discovery across relevant sources
3. Monitor progress and handle errors
4. Filter results by quality threshold
5. Update workflow_state and memory blocks
6. Format and return structured results
7. Suggest next steps

Key principles:

• Always check if question exists first
• Update workflow_state throughout
• Handle source failures gracefully
• Filter by quality thresholds
• Provide structured, actionable results

Success metric: User gets high-quality, relevant papers quickly with clear next-step options.