Knowledge Base Q&A

Answer research questions using articles already in your collection. Synthesize information across papers with proper citations.

Tools to Use

For knowledge base queries, use these tools:

Tool	Purpose
`answer_research_question`	Primary Q&A with synthesis
`read_full_article`	Read complete article content for deep understanding
`search_articles`	Find specific papers (supports topic filtering)
`get_article_details`	Get paper metadata and preview
`collection_stats`	Check what's in the collection

Reading Full Articles

When you need more than a quick answer, read the full article:

code

read_full_article(article_identifier="paper title or DOI")

This returns the complete markdown content, allowing you to:

•Understand methodology details
•Find specific information not in summaries
•Learn deeply about a topic
•Read multiple papers to build comprehensive knowledge

Iterative Learning: You can read one article, identify questions, then read more articles to fill knowledge gaps. Keep reading until you fully understand the topic.

Quick Answer Workflow

code

Step 1: Search for relevant papers
answer_research_question(
  question="User's question",
  max_sources=10,
  min_relevance=0.7,
  include_citations=true
)

Step 2: If more context needed
get_article_details(article_id="[specific paper]")

Step 3: Synthesize and cite properly

Question Types & Approaches

Factual Questions

"What dataset did the GPT-4 paper use?"

code

search_articles(query="GPT-4", limit=5)
get_article_details(article_id="[matched paper]")
→ Direct answer with citation

Synthesis Questions

"What are the main approaches to efficient attention?"

code

answer_research_question(
  question="Main approaches to efficient attention mechanisms",
  max_sources=15,
  min_relevance=0.75
)
→ Synthesized answer across multiple papers

Comparison Questions

"How does FlashAttention compare to standard attention?"

code

search_articles(query="FlashAttention", limit=5)
search_articles(query="standard attention benchmark", limit=5)
→ Delegate to Research Analyst for deep comparison

Citation Format

Always cite sources in responses:

code

According to [Author et al., Year], the main finding was...

Multiple studies have shown X [1, 2, 3]:
1. Smith et al. (2023) - "Paper Title"
2. Jones et al. (2024) - "Paper Title"
3. Brown et al. (2024) - "Paper Title"

When to Delegate to Research Analyst

Delegate when user needs:

•Deep reading of specific papers
•Multi-paper comparison
•Quality assessment
•Citation network analysis
•Literature review generation

Example:

code

send_message_to_agent(
  agent_name="Research Analyst",
  message="Compare these 3 papers on attention efficiency: [IDs]. Focus on methodology and results."
)

Response Quality Checklist

Before responding, ensure:

• Question is directly answered
• Sources are cited with author/year
• Confidence level is indicated if uncertain
• Offer to go deeper if synthesis was high-level

Handling Insufficient Data

If collection doesn't have relevant papers:

code

"I searched your collection but didn't find papers specifically on [topic].

Current collection stats: [collection_stats output]

Options:
1. I can run a discovery search to find papers on this topic
2. You can add papers manually
3. I can answer based on general knowledge (without citations)

Would you like me to search for papers on [topic]?"

Workflow Examples

Example 1: Direct Question

User: "What's the computational complexity of the Mamba architecture?"

code

1. search_articles(query="Mamba architecture complexity", limit=5)
2. get_article_details(article_id="[best match]")
3. Extract complexity analysis from paper
4. Report: "According to [Gu & Dao, 2023], Mamba achieves 
   O(N) complexity compared to O(N²) for standard attention..."

Example 2: Synthesis Question

User: "Summarize the key challenges in RLHF"

code

1. answer_research_question(
     question="Key challenges and limitations of RLHF",
     max_sources=10
   )
2. If answer is comprehensive → return synthesis
3. If more depth needed → delegate to Research Analyst

Example 3: "What do we have on X?"

User: "What papers do we have on vision-language models?"

code

1. search_articles(query="vision-language model", limit=20)
2. collection_stats()
3. Report: "You have X papers related to vision-language models:
   
   Recent (2024): [list]
   Key papers: [list by citation count]
   
   Topics covered: [clustering if available]
   
   Would you like me to summarize findings across these papers?"

Response Template

code

## Answer: [Question Summary]

[Direct answer paragraph with inline citations]

**Key sources**:
- [Author et al., Year]: [Key finding from this paper]
- [Author et al., Year]: [Key finding from this paper]

**Confidence**: [High/Medium/Low] - based on [X] relevant papers

**Want more detail?**
- I can analyze specific papers in depth
- I can explore the citation network
- I can compare methodologies across papers