Research Query Management

Ask these questions:

1. "What topic do you want to track?"
2. "How often do you want updates?" (daily/weekly)
3. "How many papers per update is manageable for you?"

Step 2: Build the Query

list_available_sources()  # Show options

create_research_question(
  title="Descriptive title for this search",
  keywords=["primary_term", "secondary_term", "synonym"],
  sources=["source1", "source2"],
  max_papers=15,
  relevance_threshold=0.7,
  schedule="daily"  # or "weekly"
)

Step 3: Test the Query

run_discovery_for_question(question_id="[new query ID]")

Review results with user:

• Are papers relevant?
• Too many/too few results?
• Missing important keywords?

Step 4: Confirm Setup

"Your recurring search is set up:

📋 **Query**: [title]
🔑 **Keywords**: [list]
📚 **Sources**: [list]
⏰ **Schedule**: [daily/weekly]
📊 **Expected**: ~[X] papers per run

The system will automatically search for new papers and add them
to your collection. You'll find new papers in your daily/weekly digest."

Refining Existing Queries

Diagnosis Questions

When user reports issues, ask:

Common Refinements

Too much noise:

get_research_question(question_id="[query ID]")

update_research_question(
  question_id="[query ID]",
  relevance_threshold=0.8,  # Raise from 0.7
  keywords=["more", "specific", "terms"]  # Add specificity
)

Missing papers:

update_research_question(
  question_id="[query ID]",
  relevance_threshold=0.65,  # Lower threshold
  sources=["add", "more", "sources"],  # Add sources
  keywords=["existing", "plus", "synonyms"]  # Add synonyms
)

Wrong domain:

update_research_question(
  question_id="[query ID]",
  keywords=["topic", "-exclude_term"],  # Negative keywords
  sources=["domain_specific_source"]  # Change sources
)

Schedule Recommendations

Query Health Check

Periodically review query performance:

list_research_questions()

For each query:
  get_research_question(question_id="...")

  Check:
  - Last run date
  - Papers found per run
  - User engagement (if tracked)

  Recommend adjustments if needed

Workflow Examples

Example 1: New Topic Tracking

User: "Keep me updated on new papers about state space models"

1. "I'll set up a recurring search for you. A few questions:
    - How often should I check for new papers? (daily/weekly)
    - How many papers can you review? (~10-15 daily or ~30-50 weekly)"

2. [User: "Weekly, about 30 papers"]

3. create_research_question(
     title="State Space Models Research Updates",
     keywords=["state space model", "SSM", "Mamba", "S4", "linear attention"],
     sources=["arxiv", "semantic_scholar"],
     max_papers=35,
     relevance_threshold=0.7,
     schedule="weekly"
   )

4. run_discovery_for_question(question_id="...")

5. "Found 28 papers in the initial test. Here are the top 5:
    [list]

    Does this look like what you're looking for?"

Example 2: Refining a Noisy Query

User: "My attention mechanisms search is giving me too many irrelevant papers"

1. list_research_questions()  # Find the query

2. get_research_question(question_id="attention-query-id")
   → Current settings: threshold=0.65, keywords=["attention"]

3. "I see your current search uses broad keywords. Let's refine:
    - What specific type of attention are you interested in?
    - Any domains you want to exclude?"

4. [User: "Just efficient attention for transformers, not general attention"]

5. update_research_question(
     question_id="attention-query-id",
     keywords=["efficient attention", "linear attention", "sparse attention", "flash attention"],
     relevance_threshold=0.75
   )

6. run_discovery_for_question(question_id="attention-query-id")

7. "Updated! Test run found 18 papers (down from 45).
    Here are the top 5 - are these more relevant?"

Example 3: Multiple Related Queries

User: "I'm researching LLM efficiency - help me set up comprehensive tracking"

1. "For comprehensive coverage, I recommend multiple focused queries:

   Query 1: Model Architecture Efficiency
   Query 2: Training Efficiency
   Query 3: Inference Optimization

   Each will capture different aspects. Shall I set these up?"

2. [Create each query with specific keywords]

3. "You now have 3 queries running weekly:
    - Architecture: ~15 papers/week
    - Training: ~20 papers/week
    - Inference: ~25 papers/week

    Total: ~60 papers/week. Manageable for your schedule?"

Response Template

For new query setup:

## Research Query Created ✓

**Title**: [query title]
**ID**: [query_id]

**Configuration**:
- Keywords: [list]
- Sources: [list]
- Schedule: [frequency]
- Max papers: [count]
- Relevance threshold: [value]

**Test Results**:
- Papers found: [count]
- Sample papers: [top 3]

**Next steps**:
- Query will run automatically on [schedule]
- Use `get_research_question(question_id="[ID]")` to check status
- Ask me to refine if results aren't quite right