| name | deep-research |
| user-invocable | true |
| allowed-tools | Read, Write, Glob, Task, perplexity-webui_pplx_ask, perplexity-webui_pplx_deep_research, kagi-search_kagi-search, AskUserQuestion |
| description | Deep research with multi-stage verification pipeline inspired by Lutum Veritas. Use for comprehensive, verified research with claim audits and cross-referencing. Triggered by "deep research", "thorough research", or "/deep-research". |
Deep Research Skill - Lutum Veritas Inspired
Trigger
- "deep research on [topic]"
- "thorough research on [topic]"
- "/deep-research [topic]"
- Any request requiring comprehensive, verified answers with sources
Core Philosophy
Key innovations from Lutum Veritas:
- Recursive context passing - Each research point knows what previous ones discovered
- Claim Audits - Self-verification instead of blind assertions
- Dual-scraping phases - First for answer, second for verification
- Source transparency - Every claim traced to its source
Mode Selection
Mode A: Quick Verify (Ask Mode)
When: User needs a verified answer, not a full research report
Time: ~60-90 seconds
Use for: Factual questions, single-topic verification
Mode B: Deep Research
When: User needs comprehensive analysis
Time: ~5-15 minutes
Use for: Complex topics, multiple angles, full reports
Ask user which mode if unclear:
- "Do you want a quick verified answer (~2 min) or comprehensive deep research (~10 min)?"
Mode A: Quick Verify Pipeline (6 Stages)
C1: Intent Analysis → C2: Knowledge Gap → C3: Search Strategy → C4: Synthesis → C5: Claim Audit → C6: Verification
Stage C1: Intent Analysis
Goal: Understand what the user really needs
Use Perplexity Ask to analyze the question:
Analyze this research question and identify:
1. Core intent - what is the user actually trying to understand?
2. Implicit requirements - what does "good answer" look like for this query?
3. Success criteria - how will we know the answer is complete?
Question: {user_question}
Stage C2: Knowledge Gap Analysis
Goal: Determine what must be searched vs. what model knows
For this question: {user_question}
What does the model's training data likely cover well?
What aspects definitely need fresh web search?
Be specific about knowledge gaps.
Stage C3: Search Strategy
Goal: Create targeted search plan
Execute parallel searches using Perplexity Search:
- Primary angle: {main_topic}
- Counter角度: {opposing_view}
- Latest updates: {topic} 2024 2025
Use Kagi as secondary source for:
- Technical docs, GitHub, forums
- Alternative viewpoints not in Perplexity
Stage C4: Answer Synthesis
Goal: Generate initial answer with inline citations
Format:
- Start with direct answer
- Use [1], [2], [3] for sources
- Distinguish established facts from interpretations
- Flag areas of uncertainty
Stage C5: Claim Audit (KEY INNOVATION)
Goal: Self-verify every claim
For each major claim in C4 output, run verification:
Claim: {specific_claim_from_answer}
Verify this claim. Search for contradictory evidence.
Return:
- VERIFIED: Source confirms claim
- CONTRADICTED: Sources disagree
- UNCERTAIN: Insufficient evidence
- NUANCED: Claim is partially true but needs qualification
This is the Lutum Veritas magic - forces self-reflection instead of blind assertions.
Stage C6: Final Verification
Goal: Cross-check against second set of sources
Search for:
- "debunks [claim]"
- "myth about [topic]"
- "[topic] false"
Final output format:
## Answer
[Synthesized answer with verified claims]
## Sources
[1] Source title - URL
[2] Source title - URL
## Verification Notes
- Claim X: VERIFIED [source]
- Claim Y: NUANCED - [qualification]
- Claim Z: UNCERTAIN - [explanation]
Mode B: Deep Research Pipeline
Clarification → Research Plan → Deep Research (per point) → Final Synthesis
Step 1: Clarification
Ask smart follow-up questions to understand scope:
To research this topic effectively, I need to clarify:
1. Scope: Are we covering history, current state, future, or all?
2. Depth: Surface overview or detailed analysis?
3. Angle: Any specific perspective (pro/con, technical, business)?
4. Audience: Expert or general?
5. Time sensitivity: Need latest 2024/2025 info?
Topic: {topic}
Use AskUserQuestion tool.
Step 2: Research Plan
Generate structured investigation points:
Create a research plan for: {topic}
Break this into 4-8 independent research points that:
- Can be researched in parallel
- Together cover the topic comprehensively
- Have clear, distinct angles
- Build on each other (later points can reference earlier)
Format:
## Research Points
### Point 1: [Title]
- Focus: [what to investigate]
- Key questions: [2-3 questions]
- Expected sources: [type of sources]
...etc
Step 3: Deep Research (Per Point)
For EACH research point, execute:
3a. Think: Generate search queries for this point
3b. Search: Run Perplexity + Kagi searches
3c. Select: Pick best 3-5 URLs
3d. Synthesize: Create "dossier" for this point
CRITICAL: Pass context forward:
Context from previous research points:
{summary_of_points_1_to_n-1}
Now researching point {n}: {title}
How does this connect to previous findings?
What new angles does this point add?
Step 4: Final Synthesis
Cross-reference all dossiers:
Synthesize all research points into a comprehensive report:
## Previous Findings (Context)
{all_point_summaries}
## New Research: Point {n}
{current_dossier}
## Cross-Reference Task
- What connects this to previous findings?
- Any contradictions?
- What's the unified picture?
Final output structure:
# Deep Research: {Topic}
## Executive Summary
{2-3 paragraph overview}
## Key Findings
### Finding 1
- Evidence: [source]
- Confidence: HIGH/MEDIUM/LOW
### Finding 2
...
## Source Registry
| # | Source | Type | Relevance |
|---|--------|------|-----------|
| 1 | Title | article | 9/10 |
...
## Areas of Uncertainty
- [List claims with lower confidence]
## Conclusion
{ synthesised answer }
Source Quality Grading
Apply Lutum Veritas quality levels:
| Level | Source Type | Reliability |
|---|
| I | Peer-reviewed academic | Highest |
| II | Official docs/ government | High |
| III | Major news / established media | High |
| IV | Industry publications | Medium |
| V | Blog posts / personal sites | Lower |
| VI | Social media / forums | Lowest |
| VII | Unknown / unverified | Avoid |
Cost Optimization (from Lutum Veritas philosophy)
- Use Perplexity Search for initial discovery (cheap)
- Use Perplexity Ask for synthesis (moderate)
- Use Kagi for technical/deep sources (secondary verification)
- Reserve Deep Research for complex topics only
Target costs:
- Quick Verify: ~5k tokens
- Deep Research: ~30-50k tokens
Verification Checklist
Before presenting any research, confirm:
Examples
Quick Verify:
- "Deep research: Is AI coding actually faster?"
- "Verify: What's the current state of Rust in web dev?"
Deep Research:
- "Do a deep research on: The true cost of AI coding assistants in enterprise"
- "Thorough research: Compare React vs Vue vs Svelte in 2025"
Fallback
If research is inconclusive:
## Limitations
- [Aspect that couldn't be verified]
- [Reason for uncertainty]
- [Recommendations for further research]
Always be honest about what couldn't be determined. This is the Lutum Veritas way - truth over confidence.