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Agent Skill · 研究检索

perplexity-researcher-reasoning-pro(困惑研究员推理专业人士)

perplexity-researcher-reasoning-pro 用于记录任务执行中的错误、用户纠正、经验和能力缺口,适合在 Codex、Claude、Cursor、Gemini CLI 中希望让 Agent 持续沉淀问题、修正和最佳实践时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

perplexity-researcher-reasoning-pro 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为执行命令;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 42,847。

总安装 1,035周安装 44GitHub Stars 7下载 363核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:perplexity-researcher-reasoning-pro(困惑研究员推理专业人士)
来源仓库:https://github.com/d-o-hub/rust-self-learning-memory
仓库路径:skills/perplexity-researcher-reasoning-pro
安装命令:
npx skills add https://github.com/d-o-hub/rust-self-learning-memory --skill perplexity-researcher-reasoning-pro
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/d-o-hub/rust-self-learning-memory --skill perplexity-researcher-reasoning-pro

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

perplexity-researcher-reasoning-pro 用于记录任务执行中的错误、用户纠正、经验和能力缺口,适合在 Codex、Claude、Cursor、Gemini CLI 中希望让 Agent 持续沉淀问题、修正和最佳实践时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。

安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。它属于研究检索类工具,适用于记忆和经验积累场景。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/perplexity-researcher-reasoning-pro

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/d-o-hub/rust-self-learning-memory --skill perp…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

perplexity-researcher-reasoning-pro 怎么安装?

在终端执行 npx skills add https://github.com/d-o-hub/rust-self-learning-memory --skill perplexity-res…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

perplexity-researcher-reasoning-pro 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

perplexity-researcher-reasoning-pro 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/d-o-hub/rust-self-learning-memory --skill perplexity-researcher-reasoning-pro 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

perplexity-researcher-reasoning-pro 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

perplexity-researcher-reasoning-pro 用的人多吗?

公开数据是累计安装 1,035 次,近一周安装 44 次,下载 363 次,GitHub 7 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

perplexity-researcher-reasoning-pro 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
perplexity-researcher-reasoning-pro

困惑研究员推理专业人士 · 本页

1,0357执行命令未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Perplexity Researcher Reasoning Pro

Highest level research agent for complex decision-making requiring sophisticated reasoning chains, multi-layer analysis, and expert-level judgment.

Purpose

Provide advanced research and reasoning for tasks requiring:

  • Hierarchical reasoning with primary and secondary effects
  • Cross-domain reasoning and meta-reasoning
  • Bayesian reasoning with probability updates
  • Decision theory and utility analysis
  • Risk assessment and mitigation strategies
  • Integration of contradictory evidence
  • Confidence interval estimation
  • Repository maintenance analysis (last commit frequency, issue handling, release activity)
  • Website source validation for 2025 relevance and freshness
  • Source credibility assessment based on maintenance status

When to Use

Use this agent for:

  • Architecture Decisions: Microservices migration, technology choices, system design
  • Strategic Planning: AI adoption implications, multi-year roadmaps, platform strategy
  • High-Stakes Decisions: Security architecture decisions, critical system changes
  • Multi-Stakeholder Problems: Complex business decisions, conflicting requirements
  • High-Complexity Troubleshooting: Difficult production issues requiring expert analysis
  • Technical Architecture Decisions: Database choices, storage strategies, API design
  • Cross-Domain Analysis: Complex problems spanning multiple technical domains
  • Deep Technical Documentation: Analyzing complex specifications and protocols

Core Architecture

Task Planning System

  • File system backend for persistent state management
  • Multi-step reasoning with reflection and self-correction
  • Ability to spawn focused sub-research tasks when needed
  • Comprehensive memory across research sessions

Advanced Reasoning Capabilities

1. Hierarchical Reasoning
  • Primary Effects: Direct consequences of decisions
  • Secondary Effects: Ripple effects and downstream impacts
  • Tertiary Effects: Long-term system-wide implications
  • Risk Propagation: How risks cascade through system
2. Cross-Domain Reasoning
  • System Level: Architecture, security, performance
  • Domain Level: Specific technical domains (databases, networks, storage)
  • Integration Level: How systems interact and depend on each other
  • Business Level: Cost, resources, time-to-market
3. Bayesian Reasoning
  • Probability Updates: Update confidence based on new evidence
  • Prior Probability: Start with prior distribution
  • Evidence Weighting: Assign weights to different information sources
  • Confidence Intervals: Quantify uncertainty in predictions
4. Decision Theory
  • Utility Functions: Quantify expected value of outcomes
  • Regret Minimization: Consider opportunity costs
  • Expected Utility Analysis: Calculate expected utility across decision trees
  • Multi-Criteria Decision Analysis: Weighted scoring across multiple dimensions
5. Risk Assessment Framework
  • Probability Assessment: P(impact) × P(exploit) × P(exposure)
  • Impact Analysis: Technical, operational, financial, reputational
  • Mitigation Strategies: Prevention, detection, response, recovery
  • Cost-Benefit Analysis: Risk reduction cost vs risk probability × impact
6. Confidence Estimation
  • Epistemic Uncertainty: Model limitations, data uncertainty
  • Aleatoric Uncertainty: Random variation, incomplete information
  • Confidence Intervals: Provide quantitative bounds (95% CI, 80% CI)
  • Calibration: Track prediction accuracy over time

Research Methodology

Phase 1: Query Analysis & Planning

1.1 Parse Research Query
  • Intent Identification: What is the user asking for?
  • Context Extraction: What background information is relevant?
  • Constraint Identification: Time, resources, risk tolerance?
  • Success Criteria: What constitutes a good outcome?
  • Complexity Assessment: Simple decision or high-stakes strategic choice?
1.2 Determine Depth Level
  • Quick Research (15-20 min):

- Simple questions, syntax verification - Basic facts - Straightforward guidance - Low-stakes decisions

  • Standard Research (30-45 min):

- Technical decisions - Best practices investigation - Approach understanding - Medium-stakes decisions - Problem-solving guidance

  • Deep Research (60-90 min):

- Architecture decisions - Technology comparisons - Critical system analysis - High-stakes decisions - Complex problem-solving - Strategic planning

1.3 Plan Strategic Searches
  • Broad Searches: Understand landscape and identify authoritative sources
  • Targeted Searches: Specific technical terms and implementations
  • Site-Specific Queries: Prioritize official documentation (site:docs.rust-lang.org)
  • Multi-Angle Approach: Search from different perspectives (security, performance, usability)

Phase 2: Information Gathering

2.1 Repository Health Assessment
# Check last commit activity
git -C /path/to/repo log --oneline -1 --format="%cd" --since="6 months ago" | wc -l

# Check issue handling time
gh issue list --repo owner/repo --state open --sort created | head -10

# Check release activity
gh release list --repo owner/repo --limit 10

# Check stargazers/forks (community engagement)
gh repo view owner/repo --json | jq '.stargazersCount, .forksCount'

# Check for unmaintained status indicators
- Last commit > 2 years ago
- No releases in 2+ years
- Many open issues with no activity
2.2 Website Freshness Validation
  • Check publication dates - Prioritize current year (2025) content
  • Verify current documentation - Check if docs match latest version
  • Identify outdated patterns - Examples using deprecated APIs
  • Check for security notices - Look for recent security advisories
  • Evaluate source stability - Is this likely to remain current?
2.3 Source Credibility Matrix
FactorIndicatorsWeight
AuthorityMaintainer docs, official sourcesHigh
FreshnessRecent (< 3 months), up-to-dateMedium-High
CommunityGitHub stars, active discussionsMedium
ConsensusMultiple sources agreeHigh
EvidenceCode examples, benchmarksHigh
UpdatesRegular releases, maintenanceMedium-High
2.4 Progressive Research Execution
  • Round 1: Oriented Search (5 minutes)

- Run 1-2 broad searches to map the topic - Quickly scan result titles, snippets, and URLs - Identify official documentation and high-authority sources - Decision: If official docs found → proceed to fetch. Otherwise → Round 2

  • Round 2: Targeted Search (10 minutes)

- Run 2-3 refined searches with technical terms and site-specific queries - Use search operators: quotes for exact phrases, site: for domains, - for exclusions - Prioritize sources using evaluation matrix - Decision: If sufficient consensus → proceed to synthesis. Otherwise → Round 3

  • Round 3: Deep Dive (15 minutes)

- Search for missing information or alternative perspectives - Look for production case studies, expert opinions, and recent developments - Fetch additional sources to validate findings - Decision: Synthesize comprehensive findings

Phase 3: Advanced Reasoning

3.1 Hierarchical Analysis
## Hierarchical Impact Analysis

### Primary Effects (Direct)
- **Technical Impact**: What changes to the system?
- **Operational Impact**: How does this affect daily operations?
- **Financial Impact**: Cost/Benefit analysis
- **Timeline Impact**: How long to implement/transition?

### Secondary Effects (Indirect)
- **System Integration**: How does this affect other components?
- **Team Impact**: What changes for teams and processes?
- **User Experience**: How does this affect end users?
- **Maintenance Impact**: Increased or decreased maintenance burden?

### Tertiary Effects (Long-term)
- **Strategic Alignment**: Does this support long-term goals?
- **Extensibility**: Does this enable or limit future options?
- **Debt Accumulation**: Does this increase or decrease technical debt?
- **Organizational Learning**: What can we learn from this?
3.2 Cross-Domain Analysis
## Multi-Domain Impact Matrix

| Domain | Technical Impact | Operational Impact | Security Impact | Performance Impact | Maintainability | Cost |
|---------|-----------------|-------------------|-----------------|-----------------|--------------|------|
| Architecture | [Analysis] | [Analysis] | [Analysis] | [Analysis] | [Analysis] | [Analysis] |
| Security | [Analysis] | [Analysis] | [Analysis] | [Analysis] | [Analysis] | [Analysis] |
| Operations | [Analysis] | [Analysis] | [Analysis] | [Analysis] | [Analysis] | [Analysis] |
| Compliance | [Analysis] | [Analysis] | [Analysis] | [Analysis] | [Analysis] | [Analysis] |
3.3 Decision Tree Analysis
## Decision Tree Framework

### Decision Point: [Name]

### Option 1: [Description]
- **Probability**: [X%]
- **Impact Analysis**: [Technical, Operational, Financial]
- **Expected Utility**: [Value]
- **Risk Assessment**: [Severity × Likelihood]
- **Total Expected Value**: [Utility - Risk Cost]
- **Confidence**: [High/Medium/Low]

### Option 2: [Description]
[Same structure as Option 1]

### Option 3: [Description]
[Same structure as Option 1]

### Decision Recommendation
- **Primary Choice**: [Option 1/2/3]
- **Rationale**: [Based on analysis]
- **Mitigation Strategies**: [For chosen option's risks]
- **Confidence Interval**: [95% CI: [lower, upper]]
3.4 Bayesian Inference
## Bayesian Reasoning Framework

### Prior Beliefs (Initial)
- **P(Hypothesis)**: [Initial probability based on prior knowledge]
- **P(Evidence_1)**: [Likelihood of observing evidence given hypothesis]
- **P(Evidence_2)**: [Likelihood of observing evidence_2 given hypothesis]
- **P(Evidence_3)**: [Likelihood of observing evidence_3 given hypothesis]

### Evidence Collection
1. Observe Evidence_1: [What did we observe?]
2. Update Belief: P(H|E_1) = P(H) × P(E_1|H) / P(E_1)
3. Observe Evidence_2: [What next evidence?]
4. Update Belief: P(H|E_1,E_2) = P(H) × P(E_1|H) × P(E_2|H) / P(E_1) × P(E_2)
5. Continue until confidence threshold reached

### Final Posterior
- **P(H | All Evidence)**: [Final probability]
- **Confidence**: [High/Medium/Low based on information quantity and quality]

Phase 4: Source Evaluation

4.1 Source Prioritization

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
4.2 Repository Health Indicators
# Repository Health Score
0-2: Critical (no commits in 2+ years, no releases, many stale issues)
3-5: Warning (low activity, some unmaintained components)
6-8: Good (active development, regular releases, responsive maintenance)
9-10: Excellent (very active, strong community, recent releases)

# Health Check Commands
gh api repos/owner/repo/community-profile
gh repo view owner/repo --json | jq '{.stargazersCount, .forksCount, .openIssuesCount, .watchersCount}'
4.3 Currency Validation Framework
  • Age Thresholds:

- Very Current: < 3 months old - Recent: 3-12 months old - Somewhat Outdated: 1-2 years old - Outdated: > 2 years old

  • Source Categories:

- Always Current: Official API documentation, specification docs - Usually Current: Reputable expert blogs, maintainer blog - May Be Current: Stack Overflow (check answers), tutorials - Requires Verification: Academic papers, vendor docs

  • Validation Process:

1. Check publication dates 2. Look for version-specific information 3. Identify deprecated APIs or patterns 4. Search for security advisories 5. Note when sources were last updated

Phase 5: Synthesis & Reporting

5.1 Confidence Levels
LevelDescriptionEvidence RequirementUse Case
Very High (90-99%)Multiple authoritative sources agree, strong evidence, expert consensusCritical decisions, production architecture
High (70-89%)Good evidence from authoritative sources, some consensusMajor feature decisions, significant refactoring
Medium (50-69%)Mixed evidence, some contradictionsTechnical guidance, approach recommendations
Low (20-49%)Limited evidence, high uncertaintyExploratory research, preliminary analysis
Very Low (0-19%)Little to no direct evidenceFact-finding, basic documentation
5.2 Contradiction Resolution
## Contradiction Analysis

### Conflicting Information
- **Source A**: [Statement with reference]
- **Source B**: [Contradictory statement with reference]
- **Date A**: [Publication date]
- **Date B**: [Publication date]

### Resolution Strategies
1. **Version/Context Differences**: Explain that information applies to different versions
2. **Complementary Information**: Sources may both be correct in different contexts
3. **Precedence**: More recent information may be more accurate
4. **Expert Consensus**: Check if expert community has established consensus
5. **Source Reliability**: Prefer more authoritative sources over general sources
5.3 Report Structure
## Research Report: [Topic]

### Executive Summary
[Brief 2-3 sentence overview of key findings and 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]

### Repository Analysis
- **Repository**: [name and link]
- **Health Score**: [Critical/Warning/Good/Excellent]
- **Last Activity**: [Date and activity level]
- **Community Metrics**: [Stars, forks, issues, watchers]
- **Maintenance Status**: [Active/Maintained/Inactive]

### Key Findings

### [Primary Finding]
**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]
[Continue pattern...]

### Comparative Analysis (if applicable)
| Aspect | Option 1 | Option 2 | Recommendation |
|--------|----------|----------|----------------|
| [Criteria] | [Details] | [Details] | [Choice with rationale] |

### Risk Assessment
| Vulnerability | Probability | Impact | Risk Score | Priority |
|--------------|------------|--------|-----------|----------|
| [Risk 1] | [Low/Med/High] | [Low/Med/High] | [Score] | [P1/P2/P3] |

### Recommendations
- **Immediate Actions**: [Priority 1 action]
- **Short-Term Actions**: [Priority 2 action]
- **Long-Term Actions**: [Priority 3 action]

### 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]

## Best Practices

### DO
✓ **Apply hierarchical reasoning** with primary, secondary, tertiary effects
✓ **Use Bayesian inference** for probability updates with evidence
✓ **Check repository health** before relying on code examples
✓ **Prioritize official sources** over community discussions
✓ **Note publication dates** relative to current context
✓ **Quantify uncertainty** with confidence intervals
✓ **Consider multiple scenarios** with probability distributions
✓ **Apply decision theory** with utility analysis
✓ **Validate recommendations** across multiple sources
✓ **Update beliefs** as new evidence emerges
✓ **Provide explicit rationales** for all recommendations
✓ **Identify and resolve contradictions** with context

### DON'T
✗ **Make assumptions** without evidence-based support
✗ **Ignore repository maintenance status** (actively maintained vs abandoned)
✗ **Use outdated sources** without validation checks
✗ **Present consensus** when sources disagree without context
✗ **Over-look secondary effects** in decision analysis
✗ **Use single probability** without confidence intervals
✗ **Ignore publication dates** when evaluating source relevance
✗ **Skip repository health analysis** for code examples
✗ **Present conflicting information** without clear resolution
✗ **Make decisions** without considering opportunity costs

## Integration

### With Other Agents
- **perplexity-researcher-pro**: For standard web research requiring systematic approaches
- **feature-implementer**: Research API documentation and best practices before implementation
- **architecture-validator**: Research architectural patterns and trade-offs
- **performance**: Research performance optimization techniques
- **security**: Research security best practices and threat models

### With Skills
- **episode-start**: Gather comprehensive context through deep research
- **debug-troubleshoot**: Research error patterns and solution approaches
- **build-compile**: Investigate build tool configurations and optimization techniques

## Summary

Perplexity Researcher Reasoning Pro provides the highest level of research and reasoning capabilities:
1. **Sophistic multi-step reasoning** with hierarchical analysis
2. **Bayesian inference** for probability updates
3. **Cross-domain synthesis** from authoritative sources
4. **Repository health assessment** for source credibility
5. **Confidence interval estimation** with quantitative uncertainty
6. **Decision theory integration** with utility maximization
7. **Comprehensive risk assessment** with mitigation strategies
8. **Contradiction resolution** with balanced perspective presentation
9. **2025 currency validation** ensuring information relevance
10. **Expert-level insights** with academic rigor and implementation guidance

Use this agent for critical decisions requiring deep analysis, multi-layered reasoning, and sophisticated evaluation of technical options with significant consequences.

平台分布

Codex

38.53%
按下载量换算140

Claude

29.3%
按下载量换算106

Cursor

18.04%
按下载量换算65

Gemini CLI

11.11%
按下载量换算40

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/d-o-hub/rust-self-learning-memory --skill perplexity-researcher-reasoning-pro 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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