
perplexity-researcher-pro
by d-o-hub
A modular Rust-based self-learning episodic memory system for AI agents, featuring hybrid storage with Turso (SQL) and redb (KV), async execution tracking, reward scoring, reflection, and pattern-based skill evolution. Designed for real-world applicability, maintainability, and scalable agent workflows.
SKILL.md
name: perplexity-researcher-pro description: Complex research requiring deeper analysis, multi-step reasoning, and sophisticated source evaluation for technical, academic, or specialized domain queries needing expert-level analysis, high-stakes decisions, or multi-layered problem solving.
Perplexity Researcher Pro
Advanced research agent for complex queries requiring expert-level analysis, multi-step reasoning, and sophisticated source evaluation.
Purpose
Provide deep research and analysis for complex technical, academic, or specialized domain queries that require:
- Multi-step logical analysis and inference
- Cross-domain knowledge synthesis
- Complex pattern recognition and trend analysis
- Enhanced fact-checking with multiple source verification
- Repository maintenance analysis (last commit frequency, issue handling, release activity)
- Website source validation for 2025 relevance and freshness
- Bias detection and balanced perspective presentation
- Technical documentation analysis with code examples
- Academic rigor with methodology evaluation
- Source credibility assessment based on maintenance status
When to Use
Use this skill for:
- Complex Technical Research: Architecture decisions, technology comparisons, API research
- Academic Research: Literature review, methodology evaluation, theoretical analysis
- Multi-Layered Problem Solving: Issues requiring multiple perspectives and deep analysis
- High-Stakes Decisions: Strategic planning, architecture migrations, technology choices
- Source Verification: Validating information across multiple sources with credibility assessment
- Repository Analysis: Evaluating library health, maintenance status, community activity
- Deep Technical Documentation: Analyzing complex APIs, protocols, specifications
Core Architecture
Task Planning
- Break down complex queries into structured research tasks
- Define clear success criteria and deliverables
- Identify information gaps and research priorities
- Plan sequential analysis with validation checkpoints
File System Backend
- Maintain persistent state management across research sessions
- Track sources, findings, and analysis progress
- Enable resumable research workflows
Multi-Step Reasoning
- Reflect on research process and self-correct
- Re-evaluate findings as new information emerges
- Identify contradictions and resolve through deeper investigation
- Apply Bayesian reasoning for probability assessment
Comprehensive Memory
- Cross-reference information across research sessions
- Learn from previous research to improve efficiency
- Track patterns in source quality and information reliability
Research Methodology
Phase 1: Planning
1. Analyze Research Query
- Parse User Intent: What is being asked?
- Identify Domain: Technical, academic, business, etc.
- Determine Scope: How deep does the analysis need to be?
- Assess Complexity: Simple, Standard, or Deep research required?
- Set Time Constraints: Quick (15-20 min), Standard (30-45 min), or Deep (60-90 min)?
2. Define Success Criteria
- Information Quality: Specific, accurate, current, well-sourced
- Analysis Depth: Multi-layered, covers all perspectives
- Credibility: Sources are authoritative and actively maintained
- Actionability: Clear recommendations with implementation guidance
Phase 2: Information Gathering
1. Strategic Searches
# Progressive search methodology
# Round 1: Broad, orienting search
websearch query: "[topic] overview 2025"
# Round 2: Targeted, specific searches
websearch query: "[topic] technical implementation guide"
websearch query: "[topic] best practices 2025"
# Round 3: Deep dive searches
websearch query: "[topic] architecture comparison analysis"
websearch query: "[topic] detailed technical documentation"
2. Source Discovery
- Official Documentation: Vendor docs, RFCs, specifications
- Expert Blogs: Recognized industry experts, engineering teams
- Academic Sources: Papers, conference proceedings, journals
- Community Resources: GitHub issues, Stack Overflow, forums
- Repositories: Source code with maintenance analysis
3. Source Evaluation Framework
Priority 1 ⭐⭐⭐ (Fetch First)
- Official documentation from maintainers
- GitHub issues/PRs from core contributors
- Production case studies from reputable companies
- Recent expert blog posts (within current year)
Priority 2 ⭐⭐ (Fetch If Needed)
- Technical blogs from recognized experts
- Stack Overflow with high votes (>50) and recent activity
- Conference presentations from domain experts
- Tutorial sites with technical depth
Priority 3 ⭐ (Skip Unless Critical)
- Generic tutorials without author credentials
- Posts older than 2-3 years for fast-moving tech
- Forum discussions without clear resolution
- Marketing/promotional content
Red Flags 🚫 (Avoid)
- AI-generated content farms
- Duplicate content aggregators
- Paywalled content without abstracts
- Sources contradicting official docs without justification
Phase 3: Content Analysis
1. Content Fetching
# Use WebFetch to retrieve full content
webfetch url: "https://official-docs-url"
# Analyze documentation structure
# Extract key sections, examples, code snippets
# Identify version information and dates
2. Repository Analysis
# Analyze repository health
# Check: Last commit frequency, recent activity
# Check: Open issues, issue handling responsiveness
# Check: Release frequency and versioning
# Check: Star/Fork count (GitHub), contributors
# Example repository health metrics
git -C /path/to/repo log --oneline -20
git -C /path/to/repo log -1 --format="%cd" --since="6 months ago"
gh repo view [owner/repo] --json | jq '.stargazersCount, .forksCount'
3. Cross-Reference and Synthesis
# Compare findings from multiple sources
# Identify consensus and disagreements
# Note version-specific information
# Highlight conflicting information with context
Phase 4: Analysis and Synthesis
1. Pattern Recognition
- Identify recurring patterns across sources
- Detect emerging trends or best practices
- Recognize anti-patterns and common mistakes
- Extract successful implementation approaches
2. Bias Detection
- Identify potential biases in sources
- Check for vendor lock-in or product promotion
- Look for conflicts of interest
- Present balanced perspectives
3. Quality Assessment
- Accuracy: Quote sources precisely
- Currency: Check publication dates (note age of information)
- Authority: Prioritize official sources and recognized experts
- Completeness: Search multiple angles, identify gaps
- Transparency: Clearly indicate uncertainty, conflicts, and limitations
4. Inference and Reasoning
# Apply multi-step logical analysis
# Use Bayesian reasoning for probability assessment
# Consider multiple hypotheses and weigh evidence
# Identify assumptions and validate them
# Reason from first principles when appropriate
Phase 5: Reporting
Report Structure
## Research Summary
[Brief 2-3 sentence overview of key findings and main recommendations]
## Research Scope
- **Query**: [Original research question]
- **Depth Level**: [Quick/Standard/Deep]
- **Sources Analyzed**: [Count and brief description]
- **Current Context**: [Date awareness and currency considerations]
## Key Findings
### [Primary Finding/Topic]
**Source**: [Name with direct link]
**Authority**: [Official/Maintainer/Expert/etc.]
**Publication**: [Date relative to current context]
**Key Information**:
- [Direct quote or specific finding with page/section reference]
- [Supporting detail or code example]
- [Additional context or caveat]
### [Secondary Finding/Topic]
[Continue pattern...]
## Comparative Analysis (if applicable)
| Aspect | Option 1 | Option 2 | Recommendation |
|--------|----------|----------|----------------|
| [Criteria] | [Details] | [Details] | [Choice with rationale] |
## Implementation Guidance
### Recommended Approach
1. **[Action 1]**: [Specific step with technical details]
2. **[Action 2]**: [Next step with considerations]
### Best Practices
- **[Practice 1]**: [Description with source attribution]
- **[Practice 2]**: [Description with context]
## Additional Resources
- **[Resource Name]**: [Direct link] - [Why valuable and when to use]
- **[Documentation]**: [Link] - [Specific section or purpose]
## Gaps & Limitations
- **[Gap 1]**: [Missing information] - [Potential impact]
- **[Limitation 1]**: [Constraint or uncertainty] - [How to address]
Research Depth Levels
Quick Research (15-20 min)
Scope: Simple questions, syntax verification, basic facts Approach:
- 2-3 well-crafted searches
- Fetch 3-5 most promising pages
- Basic synthesis of findings
Stopping Criteria:
- ✅ Consensus found from 3+ authoritative sources
- ✅ Official guidance located
- ✅ Clear actionable answer achieved
Standard Research (30-45 min)
Scope: Technical decisions, best practices, approach understanding Approach:
- Progressive: Broad → Targeted → Deep dive
- Fetch 5-8 authoritative sources
- Cross-reference findings
- Consider multiple perspectives
Stopping Criteria:
- ✅ Comprehensive understanding achieved
- ✅ Multiple authoritative sources aligned
- ✅ Implementation guidance clear
- ✅ Conflicts identified and resolved
Deep Research (60-90 min)
Scope: Architecture decisions, solution comparisons, critical systems Approach:
- Full progressive search sequence
- Extensive source analysis
- Repository health assessment
- Production case studies
- Academic literature review (if applicable)
Stopping Criteria:
- ✅ Exhaustive coverage of topic
- ✅ Expert consensus identified
- ✅ Multiple solution approaches analyzed
- ✅ Risk assessment complete
- ✅ Migration path documented
Specialized Research Domains
API/Library Documentation
# Search strategy
websearch query: "[library] official documentation [specific feature]"
websearch query: "[library] [feature] example code"
websearch query: "[library] changelog [current year]"
# Source prioritization
# Priority 1: Official docs (maintainer documentation)
# Priority 2: Repository README and examples
# Priority 3: Expert tutorials and blog posts
# Priority 4: Stack Overflow with high votes
Best Practices & Recommendations
# Search strategy
websearch query: "[topic] best practices [current year]"
websearch query: "[topic] patterns" site:blog.[expert].com"
websearch query: "[topic] anti-patterns" vs "best practices"
# Cross-reference
websearch query: "[option1] vs [option2] performance comparison"
websearch query: "[old tech] to [new tech] migration guide"
Technical Problem Solving
# Specific error terms
websearch query: "[exact error message]" solution
# Search forums
websearch query: "[problem]" site:stackoverflow.com
# Find GitHub solutions
websearch query: "[issue]" site:github.com/[repo]
# Find blog posts
websearch query: "[problem] [library] solution"
Technology Comparisons
# Direct comparisons
websearch query: "[tech1] vs [tech2] performance comparison"
# Migration guides
websearch query: "[old tech] to [new tech]" migration guide
# Benchmarks
websearch query: "[tech1] [tech2] benchmark [current year]"
Quality Standards
Research Rigor
- Accuracy: Quote sources precisely with direct links
- Currency: Always check environment context for current date; prioritize recent sources for evolving tech
- Authority: Weight official documentation and recognized experts higher
- Completeness: Search multiple angles; validate findings across sources
- Transparency: Clearly indicate uncertainty, conflicts, and source limitations
Source Attribution
- Provide direct links to specific sections when possible
- Include publication dates and version information
- Note source credibility and potential biases
- Distinguish between official guidance and community opinions
Bias Detection
- Identify potential vendor lock-in or product promotion
- Check for conflicts of interest
- Present balanced perspectives from multiple sources
- Flag assumptions explicitly
- Consider alternative viewpoints
Stopping Criteria
Complete Research When:
- ✅ Consensus Found: 3+ authoritative sources agree on approach
- ✅ Official Guidance Located: Found maintainer recommendations or official docs
- ✅ Actionable Path Clear: Have specific next steps and implementation guidance
- ✅ Time Limit Reached: Hit depth-appropriate time-box with adequate information
Continue Research If:
- ⚠️ Conflicting Information: Sources disagree without version/context explanation
- ⚠️ Outdated Sources Only: All sources >2 years old for fast-moving tech
- ⚠️ No Official Source: Haven't found maintainer or official documentation
- ⚠️ Unclear Actionability: Can't determine specific next steps
- ⚠️ Conflicting Information: Sources disagree without version/context explanation
Best Practices
DO:
✓ Check environment context for current date before all research ✓ Use current year in searches for best practices and evolving technologies ✓ Apply progressive search strategy to avoid over-researching simple queries ✓ Prioritize official sources and cross-reference findings ✓ Provide direct links with specific section references when possible ✓ Note publication dates relative to current context ✓ Be transparent about source limitations and research gaps ✓ Focus on actionable insights with concrete examples ✓ Assess repository health: Check maintenance status, commit frequency, issue responsiveness ✓ Validate dates: Note when sources were last updated relative to current context
DON'T:
✗ Stop at first results without validation from multiple sources ✗ Ignore publication dates when evaluating source relevance ✗ Trust unverified sources without authority assessment ✗ Make assumptions without evidence-based support ✗ Omit source attribution or direct links ✗ Over-research simple questions - match depth to query complexity ✗ Present conflicting information without clear context or resolution ✗ Consider only recent sources - older sources may still be valuable for stable topics ✗ Ignore repository maintenance status - inactive repos may indicate abandoned projects
Integration
With Other Agents
- websearch-researcher: For standard web research requiring systematic approaches
- feature-implementer: Research API documentation and best practices before implementation
- debugger: Research error patterns and solution approaches
- architecture-validator: Research architectural patterns and trade-offs
- performance: Research performance optimization techniques
With Skills
- agent-coordination: For coordinating multi-researcher tasks
- episode-start: Gather comprehensive context through deep research
- debug-troubleshoot: Research error patterns and solution approaches
Summary
Perplexity Researcher Pro provides:
- Multi-step logical analysis with inference and self-correction
- Cross-domain knowledge synthesis from authoritative sources
- Complex pattern recognition across technical domains
- Enhanced fact-checking with multiple source verification
- Repository maintenance analysis for source credibility assessment
- Bias detection and balanced perspective presentation
- 2025 currency validation ensuring information relevance
- Expert-level insights with academic rigor and implementation guidance
Use this agent for complex research requiring deeper analysis, multi-step reasoning, and sophisticated source evaluation beyond standard web research capabilities.
Score
Total Score
Based on repository quality metrics
SKILL.mdファイルが含まれている
ライセンスが設定されている
100文字以上の説明がある
GitHub Stars 100以上
1ヶ月以内に更新
10回以上フォークされている
オープンIssueが50未満
プログラミング言語が設定されている
1つ以上のタグが設定されている
Reviews
Reviews coming soon



