Interview Outline Master V2
Deep guides for research, cases & consulting
Description
Three primary scenario routes: 🎓 Scenario A | Academic papers (theses and journal articles), including research-question mapping and guidance against leading questions 📚 Scenario B | Case development (professional master's projects and teaching cases), including key-event timelines and triangulation 💼 Scenario C | Commissioned research and consulting (business and government projects), following the current state–problems–causes–needs–recommendations framework Four respondent sub-routes automatically adapt wording, ethical requirements, and sensitive-topic preparation for government officials, business executives, frontline employees or customers, and academic experts. Pre-interview materials request list: Send it with the invitation to request materials for refining the outline; when no materials are available, automatically supplement with public-source research. Ready-to-use structure: Each probing point explains “what to uncover” and includes five follow-up strategies (clarify/deepen/compare/hypothesize/paradox), informed-consent ethics language, and time planning.
Related Skills
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Dialogue Director Pro | Interview Design Engine
This isn't just a list of questions; it helps you design a memorable conversation. A 7-step process, from guest research to finalized materials: Guest Profile → Narrative Structure → Question Matrix → Process Layout → Interview Rehearsal → Material Conversion → Interview Debriefing 💡 Steps 1-3 form the core design process, delivering a complete interview plan independently; Steps 4-7 enhance the experience and can be used as needed. 🔍 Guest Profile | Online search of publicly available guest information generates a five-dimensional in-depth profile—factual skeleton, story vein, core conflict, communication style, and emotional entry point—telling you which direction to dig. Non-public figures automatically switch to interview-style information gathering. 🌿 Follow-up Question Branching Tree | When generating questions, the system pre-predicts the possible directions of the guest's answers for each key question and designs corresponding follow-up questions. You take this "decision tree" to the event, listen to the guest's answer, and then choose the corresponding branch to ask follow-up questions—no need for on-site AI, no need for real-time text transcription; all plans are designed during the preparation stage. It lets you be a chess player on-site, not an improvisational actor. No similar function exists on the market. 🎬 AI Rehearsal | Before the interview, AI plays the role of a guest, simulating three answering styles (in-depth/superficial/evasive), allowing you to practice follow-up questions and identify blind spots in the process. 📝 Five Outputs | Generates from a single interview: interview article/ podcast script/ oral history transcript/ social media content package/documentary script skeleton. 📊 Interview Debriefing | Plan vs. reality comparison, analysis of gold mines and regrets, five-dimensional capability radar chart, allowing you to grow with every interview. Suitable for: podcast interviews, interviews, student interviews, UX in-depth interviews, executive interviews.
Workplace Script Generator
Need to reject a candidate after five rounds of interviews? Need to send a layoff notice to an employee who's been with the company for three years? Need to negotiate salary with HR but afraid of saying the wrong thing? No one has taught you how to handle these situations – being too harsh hurts people, being too soft is ineffective, and getting it wrong could even lead to legal trouble. Choose a scenario, tell it the situation, and instantly get multiple professional scripts – for Chinese big companies, small/medium companies, English North American companies, and startups. Formal, friendly, or aspirational – pick the tone you need. ✨ Core Capabilities 1. 6 major HR scenarios: rejection letters, layoff notices, salary negotiation, interview scripts, reference checks, daily HR communication 2. Bilingual + multiple styles: Chinese big company/small-medium companies, English North American/startups – 2-3 versions per scenario 3. Context matching: 4 types of layoff reasons (strategic adjustment, bottom elimination, economic downturn, culture fit) each with specific scripts 4. Salary negotiation dual perspective: 5-level HR undercutting scripts + candidate negotiation scripts – both sides can use 5. Legal safety: all scripts are lawful, do not encourage concealment or fraud 📱 Applicable Scenarios - Startup founders/managers: learn how to properly reject, lay off, or negotiate salary - HR professionals: need quick access to different style scripts - Job seekers: understand HR script implications, negotiate with confidence - Freelancers: use professional scripts to manage client relationships from start to end The hardest part isn't making the decision – it's saying it. Let professional scripts help you speak.
Grant Proposal Review PRO V2.0
🎯 Core Functionality Overview This is an intelligent review and optimization system specially designed for national social science, education ministry, and provincial grant applications. It simulates the thinking mode of a senior review expert with 15 years of experience, ensuring academic rigor and competitiveness through three core mechanisms. 🔧 Three Core Mechanisms 1️⃣ 12-Step Structured Methodology Covers the full lifecycle of grant proposal review: Phase 1-3: Basic Diagnosis - In-depth analysis of announcement (funding priorities, review criteria, application requirements) - Cross-disciplinary type judgment (precise identification of 8 types) - Research GAP five-dimension identification (theory/methodology/empirical/policy/technology) Phase 4-7: Core Element Review - Research question TMAQ model analysis (theory/methodology/approach/question four dimensions) - Research objective SMART principle test - Research content framework completeness assessment - Research approach type matching (6 types) Phase 8-10: Deep Quality Enhancement - Precise extraction of key difficulties (distinguish criteria + breakthrough paths) - Innovation point seven-dimension mining - Feasibility seven-dimension argumentation Phase 11-12: Overall Optimization - Nine-dimension quality check (academic rigor, innovativeness, feasibility, etc.) - Comprehensive optimization suggestions and final report 2️⃣ Dual-Core Adversarial Mechanism (Builder vs Supervisor) Working Principle: - Builder (academic writer): Generates optimization plans based on user materials - Supervisor (top journal reviewer): Challenges Builder's plans with the strictest standards - Adversarial iteration: 3 rounds of confrontation to ensure plans are robust Application Scenarios: - Innovation point mining: Builder proposes innovation points → Supervisor questions novelty → iterative optimization - Feasibility argumentation: Builder designs plan → Supervisor challenges feasibility → supplementary argumentation - Literature citation: Builder cites literature → Supervisor verifies authenticity → ensure academic standards 3️⃣ Literature Authenticity Verification Mechanism Two working modes: Mode A: Placeholder Mode (Default) - Use markers like [Literature Placeholder-001] in place of specific references - Output a Literature Requirement List specifying search requirements for each placeholder - User searches and fills in real references Mode B: Real-Time Verification Mode - Call Google Scholar to verify literature authenticity in real time - Generate Literature Verification Report (authenticity/relevance/authority scores) - Ensure every citation is traceable Preventing AI Hallucination: - Prohibits fabricating authors, journals, DOIs - All references must be verified or marked as placeholders - Guarantees academic integrity bottom line 💡 Core Value and Applicable Scenarios ✅ Key Pain Points Addressed 1. Academic sloppiness: AI-generated content often includes fake references, logical gaps 2. Insufficient innovation: Difficulty uncovering true academic innovation points 3. Weak feasibility: Research plans lack systematic argumentation 4. Cross-disciplinary difficulty: Interdisciplinary topics often fall between two stools 🎓 Target Users - University faculty (social sciences, education, humanities) - Researchers (applying for national and provincial grants) - Academic teams (needing systematic review processes) 📋 Typical Workflow 1. Input: Upload announcement + proposal draft 2. Review: System executes 12-step structured analysis 3. Adversarial: Dual-core mechanism iteratively optimizes key sections 4. Verification: Literature authenticity check 5. Output: Complete review report + optimization suggestions + literature list 🔍 Differences from Traditional Review | Dimension | Traditional Human Review | Expert Review System | |-----------|------------------------|----------------------| | Review depth | Depends on personal experience | 12-step structured + 9D QC | | Academic rigor | Hard to fully audit | Literature verification + dual-core adversarial | | Innovation mining | Subjective judgment | 7-dimension systematic analysis | | Feasibility argumentation | Experience-driven | 7-dimension item-by-item argumentation | | Consistency | Varies by individual | Standardized process | | Efficiency | Days to weeks | 1-2 hours for initial review | The core advantage of this system is: it makes the tacit knowledge of a 15-year senior review expert explicit, structured, and replicable, enabling every user to receive top-level expert review services.
Interview Outline Master V2
Deep guides for research, cases & consulting
Description
Three primary scenario routes: 🎓 Scenario A | Academic papers (theses and journal articles), including research-question mapping and guidance against leading questions 📚 Scenario B | Case development (professional master's projects and teaching cases), including key-event timelines and triangulation 💼 Scenario C | Commissioned research and consulting (business and government projects), following the current state–problems–causes–needs–recommendations framework Four respondent sub-routes automatically adapt wording, ethical requirements, and sensitive-topic preparation for government officials, business executives, frontline employees or customers, and academic experts. Pre-interview materials request list: Send it with the invitation to request materials for refining the outline; when no materials are available, automatically supplement with public-source research. Ready-to-use structure: Each probing point explains “what to uncover” and includes five follow-up strategies (clarify/deepen/compare/hypothesize/paradox), informed-consent ethics language, and time planning.
Related Skills
View allDialogue Director Pro | Interview Design Engine
This isn't just a list of questions; it helps you design a memorable conversation. A 7-step process, from guest research to finalized materials: Guest Profile → Narrative Structure → Question Matrix → Process Layout → Interview Rehearsal → Material Conversion → Interview Debriefing 💡 Steps 1-3 form the core design process, delivering a complete interview plan independently; Steps 4-7 enhance the experience and can be used as needed. 🔍 Guest Profile | Online search of publicly available guest information generates a five-dimensional in-depth profile—factual skeleton, story vein, core conflict, communication style, and emotional entry point—telling you which direction to dig. Non-public figures automatically switch to interview-style information gathering. 🌿 Follow-up Question Branching Tree | When generating questions, the system pre-predicts the possible directions of the guest's answers for each key question and designs corresponding follow-up questions. You take this "decision tree" to the event, listen to the guest's answer, and then choose the corresponding branch to ask follow-up questions—no need for on-site AI, no need for real-time text transcription; all plans are designed during the preparation stage. It lets you be a chess player on-site, not an improvisational actor. No similar function exists on the market. 🎬 AI Rehearsal | Before the interview, AI plays the role of a guest, simulating three answering styles (in-depth/superficial/evasive), allowing you to practice follow-up questions and identify blind spots in the process. 📝 Five Outputs | Generates from a single interview: interview article/ podcast script/ oral history transcript/ social media content package/documentary script skeleton. 📊 Interview Debriefing | Plan vs. reality comparison, analysis of gold mines and regrets, five-dimensional capability radar chart, allowing you to grow with every interview. Suitable for: podcast interviews, interviews, student interviews, UX in-depth interviews, executive interviews.
Workplace Script Generator
Need to reject a candidate after five rounds of interviews? Need to send a layoff notice to an employee who's been with the company for three years? Need to negotiate salary with HR but afraid of saying the wrong thing? No one has taught you how to handle these situations – being too harsh hurts people, being too soft is ineffective, and getting it wrong could even lead to legal trouble. Choose a scenario, tell it the situation, and instantly get multiple professional scripts – for Chinese big companies, small/medium companies, English North American companies, and startups. Formal, friendly, or aspirational – pick the tone you need. ✨ Core Capabilities 1. 6 major HR scenarios: rejection letters, layoff notices, salary negotiation, interview scripts, reference checks, daily HR communication 2. Bilingual + multiple styles: Chinese big company/small-medium companies, English North American/startups – 2-3 versions per scenario 3. Context matching: 4 types of layoff reasons (strategic adjustment, bottom elimination, economic downturn, culture fit) each with specific scripts 4. Salary negotiation dual perspective: 5-level HR undercutting scripts + candidate negotiation scripts – both sides can use 5. Legal safety: all scripts are lawful, do not encourage concealment or fraud 📱 Applicable Scenarios - Startup founders/managers: learn how to properly reject, lay off, or negotiate salary - HR professionals: need quick access to different style scripts - Job seekers: understand HR script implications, negotiate with confidence - Freelancers: use professional scripts to manage client relationships from start to end The hardest part isn't making the decision – it's saying it. Let professional scripts help you speak.
Grant Proposal Review PRO V2.0
🎯 Core Functionality Overview This is an intelligent review and optimization system specially designed for national social science, education ministry, and provincial grant applications. It simulates the thinking mode of a senior review expert with 15 years of experience, ensuring academic rigor and competitiveness through three core mechanisms. 🔧 Three Core Mechanisms 1️⃣ 12-Step Structured Methodology Covers the full lifecycle of grant proposal review: Phase 1-3: Basic Diagnosis - In-depth analysis of announcement (funding priorities, review criteria, application requirements) - Cross-disciplinary type judgment (precise identification of 8 types) - Research GAP five-dimension identification (theory/methodology/empirical/policy/technology) Phase 4-7: Core Element Review - Research question TMAQ model analysis (theory/methodology/approach/question four dimensions) - Research objective SMART principle test - Research content framework completeness assessment - Research approach type matching (6 types) Phase 8-10: Deep Quality Enhancement - Precise extraction of key difficulties (distinguish criteria + breakthrough paths) - Innovation point seven-dimension mining - Feasibility seven-dimension argumentation Phase 11-12: Overall Optimization - Nine-dimension quality check (academic rigor, innovativeness, feasibility, etc.) - Comprehensive optimization suggestions and final report 2️⃣ Dual-Core Adversarial Mechanism (Builder vs Supervisor) Working Principle: - Builder (academic writer): Generates optimization plans based on user materials - Supervisor (top journal reviewer): Challenges Builder's plans with the strictest standards - Adversarial iteration: 3 rounds of confrontation to ensure plans are robust Application Scenarios: - Innovation point mining: Builder proposes innovation points → Supervisor questions novelty → iterative optimization - Feasibility argumentation: Builder designs plan → Supervisor challenges feasibility → supplementary argumentation - Literature citation: Builder cites literature → Supervisor verifies authenticity → ensure academic standards 3️⃣ Literature Authenticity Verification Mechanism Two working modes: Mode A: Placeholder Mode (Default) - Use markers like [Literature Placeholder-001] in place of specific references - Output a Literature Requirement List specifying search requirements for each placeholder - User searches and fills in real references Mode B: Real-Time Verification Mode - Call Google Scholar to verify literature authenticity in real time - Generate Literature Verification Report (authenticity/relevance/authority scores) - Ensure every citation is traceable Preventing AI Hallucination: - Prohibits fabricating authors, journals, DOIs - All references must be verified or marked as placeholders - Guarantees academic integrity bottom line 💡 Core Value and Applicable Scenarios ✅ Key Pain Points Addressed 1. Academic sloppiness: AI-generated content often includes fake references, logical gaps 2. Insufficient innovation: Difficulty uncovering true academic innovation points 3. Weak feasibility: Research plans lack systematic argumentation 4. Cross-disciplinary difficulty: Interdisciplinary topics often fall between two stools 🎓 Target Users - University faculty (social sciences, education, humanities) - Researchers (applying for national and provincial grants) - Academic teams (needing systematic review processes) 📋 Typical Workflow 1. Input: Upload announcement + proposal draft 2. Review: System executes 12-step structured analysis 3. Adversarial: Dual-core mechanism iteratively optimizes key sections 4. Verification: Literature authenticity check 5. Output: Complete review report + optimization suggestions + literature list 🔍 Differences from Traditional Review | Dimension | Traditional Human Review | Expert Review System | |-----------|------------------------|----------------------| | Review depth | Depends on personal experience | 12-step structured + 9D QC | | Academic rigor | Hard to fully audit | Literature verification + dual-core adversarial | | Innovation mining | Subjective judgment | 7-dimension systematic analysis | | Feasibility argumentation | Experience-driven | 7-dimension item-by-item argumentation | | Consistency | Varies by individual | Standardized process | | Efficiency | Days to weeks | 1-2 hours for initial review | The core advantage of this system is: it makes the tacit knowledge of a 15-year senior review expert explicit, structured, and replicable, enabling every user to receive top-level expert review services.
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