NSFC Writing Coach Enhanced
9-step proposal coach with reviewer checks
Description
Derived from multiple NSFC application guide books, several successfully funded proposals, and hands-on writing experience from five General Projects, this full-process interactive coach embodies the dual roles of 'Senior Chief Editor' and 'Intercepting Reviewer.' It integrates Wang Laigui's System Philosophy, Xu Changqing's 22 Proposal Song Verses, Huang Zhonglian's 250-Question Error-Checking Rules, and the latest 2026 NSFC policies. 🎯 Core Positioning: Like a senior reviewer by your side, polishing your proposal from topic selection to submission, sentence by sentence. 🔧 Three Core Mechanisms ① Ten-stage full-link engine (S1 Topic Selection → S2 Project Rationale → S3 Scientific Question Refinement → S4 Research Content → S5 Plan/Technical Route/Innovation → S6 Research Foundation → S7 Compliance Self-Check → S8 Abstract Final Review → S9 Global Quality Inspection & Export → S10 Reviewer Simulation Defense), each stage delivers a 'readable draft + structured PACK + self-check conclusion' combo, strictly step-lock progression. ② Six reviewer-level guardrails: 🔍 Three-state literature annotation (Verified/Unverified/Placeholder only, never fabricated) ｜ 🧭 Anti-drift triangle interlocking (Title ↔ Gap ↔ KSQ ↔ Objective ↔ Content ↔ Method ↔ Innovation ↔ Foundation chain lock) ｜ 🚫 High-risk wording interception (automatically rewrite landmines like 'first-ever' or 'fill the gap') ｜ ✅ Five compliance self-checks ｜ ⚖️ Ethical writing tiering ｜ 🎯 Single-module refinement. ③ Multi-core confrontation engine: A Core execution + B Core audit + E Core evolution, three cores run independently to ensure each stage's output undergoes independent audit. 💡 Differentiated Advantages · Not a template filler — it's a coach that stops you, questions you, and pushes you to revise thoroughly. · No fabricated literature — three-state literature management, unverified never enters the official version. · No topic drift — anti-drift triangle + full-chain interlocking to prevent disconnect. · No one-size-fits-all — automatic tiering by Young Scientists Fund/General Program/Regional Fund for precise adaptation. · Three major rule libraries: Wang Laigui's System Philosophy + Xu Changqing's 22 Proposal Song Verses + Huang Zhonglian's 250-Question Error-Checking Rules. · 2026 policy alignment: Four types of scientific question attribute declarations + AI usage compliance statement. 🎓 Applicable users: NSFC applicants (covering Young Scientists Fund, General Program, and Regional Fund) who aim to write a submission-ready proposal that withstands reviewer scrutiny sentence by sentence. 📋 Two entry points: 'Have a preliminary topic' — start polishing directly ｜ 'Only a vague idea' — provide keywords and get 5 candidate topics laid out.
Related Skills
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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.
ResearchNSFC App Writing Coach (Trial)
A lightweight step-by-step coach derived from multiple NSFC application guidebooks, analysis of successful funded proposals, and real writing experience from five NSFC General Projects. It begins with a checkable web questionnaire to quickly collect application category, discipline, and initial idea. Then it proceeds through a six-step main chain with step-lock: Define Title → Project Rationale → Research Objectives and Key Scientific Questions → Research Content → Innovation in Approach → Basic Compliance & Abstract Wrap-up. This ensures no skipping steps, no fabricated references or data, no unsubstantiated claims of innovation, and full chain linkage to prevent disjointedness. Designed for first-time applicants or those who want to quickly navigate the NSFC main chain—low barrier to entry, producing a solid draft that can be submitted.
WriteNSFC Grant Rev Optimizer v2.0
Turn your NSFC grant application into a winning proposal. This is a dual-engine tool that simulates a panel review, addressing two key pain points: "can't spot issues" and "don't know how to fix them". 🔴 Panel Review Perspective Rates your application A/B/C/D based on NSFC's five dimensions (scientific value, innovation, feasibility, research foundation, academic standards), revealing fatal blind spots that only surface during review. 🔵 Optimization Mentor Perspective Outputs a side-by-side "original vs revised" comparison for each paragraph, including key sections like the abstract, research questions, and innovation points—areas reviewers focus on within the first 3 minutes. ✨ Key difference: It doesn't just tell you what's wrong—it tells you how to fix it. 🚀 How to use? Paste your application text (or any section) directly. The engine automatically runs a four-step cycle: 📋 Application Profile → 🔍 Logic Stress Test → ✍️ Paragraph Refinement → 🎁 Final Delivery No additional commands needed. 📌 Suitable for Researchers applying for Young Scientists, General, or Key Programs of NSFC, as well as provincial natural science funds.
NSFC Writing Coach Enhanced
9-step proposal coach with reviewer checks
Description
Derived from multiple NSFC application guide books, several successfully funded proposals, and hands-on writing experience from five General Projects, this full-process interactive coach embodies the dual roles of 'Senior Chief Editor' and 'Intercepting Reviewer.' It integrates Wang Laigui's System Philosophy, Xu Changqing's 22 Proposal Song Verses, Huang Zhonglian's 250-Question Error-Checking Rules, and the latest 2026 NSFC policies. 🎯 Core Positioning: Like a senior reviewer by your side, polishing your proposal from topic selection to submission, sentence by sentence. 🔧 Three Core Mechanisms ① Ten-stage full-link engine (S1 Topic Selection → S2 Project Rationale → S3 Scientific Question Refinement → S4 Research Content → S5 Plan/Technical Route/Innovation → S6 Research Foundation → S7 Compliance Self-Check → S8 Abstract Final Review → S9 Global Quality Inspection & Export → S10 Reviewer Simulation Defense), each stage delivers a 'readable draft + structured PACK + self-check conclusion' combo, strictly step-lock progression. ② Six reviewer-level guardrails: 🔍 Three-state literature annotation (Verified/Unverified/Placeholder only, never fabricated) ｜ 🧭 Anti-drift triangle interlocking (Title ↔ Gap ↔ KSQ ↔ Objective ↔ Content ↔ Method ↔ Innovation ↔ Foundation chain lock) ｜ 🚫 High-risk wording interception (automatically rewrite landmines like 'first-ever' or 'fill the gap') ｜ ✅ Five compliance self-checks ｜ ⚖️ Ethical writing tiering ｜ 🎯 Single-module refinement. ③ Multi-core confrontation engine: A Core execution + B Core audit + E Core evolution, three cores run independently to ensure each stage's output undergoes independent audit. 💡 Differentiated Advantages · Not a template filler — it's a coach that stops you, questions you, and pushes you to revise thoroughly. · No fabricated literature — three-state literature management, unverified never enters the official version. · No topic drift — anti-drift triangle + full-chain interlocking to prevent disconnect. · No one-size-fits-all — automatic tiering by Young Scientists Fund/General Program/Regional Fund for precise adaptation. · Three major rule libraries: Wang Laigui's System Philosophy + Xu Changqing's 22 Proposal Song Verses + Huang Zhonglian's 250-Question Error-Checking Rules. · 2026 policy alignment: Four types of scientific question attribute declarations + AI usage compliance statement. 🎓 Applicable users: NSFC applicants (covering Young Scientists Fund, General Program, and Regional Fund) who aim to write a submission-ready proposal that withstands reviewer scrutiny sentence by sentence. 📋 Two entry points: 'Have a preliminary topic' — start polishing directly ｜ 'Only a vague idea' — provide keywords and get 5 candidate topics laid out.
Related Skills
View allGrant 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.
ResearchNSFC App Writing Coach (Trial)
A lightweight step-by-step coach derived from multiple NSFC application guidebooks, analysis of successful funded proposals, and real writing experience from five NSFC General Projects. It begins with a checkable web questionnaire to quickly collect application category, discipline, and initial idea. Then it proceeds through a six-step main chain with step-lock: Define Title → Project Rationale → Research Objectives and Key Scientific Questions → Research Content → Innovation in Approach → Basic Compliance & Abstract Wrap-up. This ensures no skipping steps, no fabricated references or data, no unsubstantiated claims of innovation, and full chain linkage to prevent disjointedness. Designed for first-time applicants or those who want to quickly navigate the NSFC main chain—low barrier to entry, producing a solid draft that can be submitted.
WriteNSFC Grant Rev Optimizer v2.0
Turn your NSFC grant application into a winning proposal. This is a dual-engine tool that simulates a panel review, addressing two key pain points: "can't spot issues" and "don't know how to fix them". 🔴 Panel Review Perspective Rates your application A/B/C/D based on NSFC's five dimensions (scientific value, innovation, feasibility, research foundation, academic standards), revealing fatal blind spots that only surface during review. 🔵 Optimization Mentor Perspective Outputs a side-by-side "original vs revised" comparison for each paragraph, including key sections like the abstract, research questions, and innovation points—areas reviewers focus on within the first 3 minutes. ✨ Key difference: It doesn't just tell you what's wrong—it tells you how to fix it. 🚀 How to use? Paste your application text (or any section) directly. The engine automatically runs a four-step cycle: 📋 Application Profile → 🔍 Logic Stress Test → ✍️ Paragraph Refinement → 🎁 Final Delivery No additional commands needed. 📌 Suitable for Researchers applying for Young Scientists, General, or Key Programs of NSFC, as well as provincial natural science funds.
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