Project Closeout Report Pro
8-Step Method + 6D Charts + Natural Language
Description
【Essential for closeout season】Create a high-quality final report in 3 hours—no more rejections! 🔥 Are you also facing these issues? → Closeout deadline approaching, not knowing where to start with years of research materials → After finishing, you realize you missed performance metrics and budget execution details → You want professional charts but don't know how to use complex tools → The generated report has an obvious 'AI smell' and you worry reviewers will notice ✅ This skill solves all these problems at once: 【Highlight 1】8-step structured workflow × Checkpoint mechanism From data collection to final draft, each step has clear guidance and confirmation. Problems are caught as they occur, not at the end. Covers all scenarios: NSFC, provincial/ministerial, and university-level projects. 【Highlight 2】One-click generation of 6 professional chart types Built-in sub-skill generators for word clouds, bar charts, line charts, and more (no extra cost). AI recommends the best chart type and generates in 30 seconds, so reviewers understand your results at a glance. 【Highlight 3】Exclusive 'de-AI-fication' optimization Four-dimensional AI trace detection + three optimization levels (conservative/moderate/aggressive). Replaces empty clichés with more specific, in-depth expressions. Optimized reports are more natural, denser, and more persuasive. 📩 Send feedback/suggestions to 1329806797@qq.com It's not about 'writing' the report, it's about 'getting the whole closeout process right.'
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Think Tank Report Writer v1.0
🎯 One sentence policy area, produce a directly submittable advisory report in 30 minutes. It's not about 'letting AI write for you,' but packaging 20 years of think tank writing methodology into an engineered pipeline—from topic selection, four-layer penetration, structured drafting to Red-Blue Team quality check, each step goes deeper than you would on your own. ━━━ Who It's For ━━━ ✅ Think tank researchers, government policy researchers, university policy researchers ✅ Writers of internal reference reports, special reports, and policy recommendation reports ✅ Experienced authors who teach advisory report writing to students/teams ━━━ 4 Core Capabilities ━━━ 🎯 Three-Dimensional Topic Scanning Pain point: Topics lack focus, angles are imprecise, recommendations are broad and fragmented. SKILL: Antenna (high-frequency verbs and gaps in policy documents) + Grounding (grassroots pain points) + Side View (horizontal comparison), outputting 3 candidate angles (A1 Problem-Oriented / A2 Comparative Reference / A3 Major Project Proposal each). 🔍 Four-Layer Penetration Analysis Pain point: Reports stay at the surface level, failing to uncover institutional roots, leading to rejection by superiors. SKILL: Phenomenon → Institution → Interests → History, layer by layer penetration. Dig three layers deeper than peers. 📋 Structured Drafting Pain point: Unfamiliar with party-government document formats, confused by three types of internal reference styles. SKILL: A1 Problem-Oriented / A2 Comparative Reference / A3 Major Project Proposal three styles; format 100% aligned with GB/T 9704-2012; out of the box. 🛡️ Red-Blue Team Adversarial Quality Check Pain point: Can't revise your own draft / Obvious AI feel / Don't know where the issues are. SKILL: Switch to reviewer perspective to critique every sentence, graded as P0 (blocks submission) / P1 (recommended fix) / P2 (optional optimization); built-in four-layer de-AI norms (banned words + sentence restructuring + language strategy + structure strategy). ━━━ 📦 One Input, Five Deliverables ━━━ Not just finished writing, but a set of reusable research assets: 1️⃣ Main report docx — 3500-5000 words, party-government document format, directly submittable 2️⃣ Topic angle candidate library — The 2 unused angles already scanned three-dimensionally, ready for next topic 3️⃣ Four-layer penetration analysis framework card — A thinking template transferable to any policy issue 4️⃣ Policy material card library — Data/policy/cases categorized and archived, an asset that grows with use 5️⃣ Red-Blue Team quality check log — Each edit includes [original text + diagnosis + revised text + rationale] ━━━ How It Works ━━━ ⚙️ Five-station pipeline, user confirmation required at each station Station 1: Three-Dimensional Topic Scanning → Station 2: Four-Layer Penetration Analysis → Station 3: Material Dehydration and Transformation → Station 4: Structured Drafting → Station 5: Red-Blue Team Quality Check ⚙️ Dashboard mechanism Each output includes a progress bar (completed / in progress / pending) + a locked parameter list to counter context drift. ⚙️ User confirmation system At the end of each station: ask if you want to proceed. Unsatisfied? You can redo until it's right. ⚙️ Fast track Experienced users with complete information can enter 'fast track' to skip pre-confirmation and go straight to drafting + quality check. ━━━ What We Don't Do (Aesthetic Lockdown) ━━━ ✕ No 'free style' option — the three special report styles have been validated by party-government organs for 20 years; free combining only leads to loss of control ✕ No 'one-click full auto' mode — five-station mandatory confirmation is a quality baseline, not a bug ✕ No delivery without fixing P0 blocking issues — quality relies on system, not luck ━━━ How to Start ━━━ Just say one sentence after opening: 'I want to write an advisory report on county-level elderly care services' 'I want to write an advisory report on financing difficulties of specialized and new enterprises' 'I want to write an advisory report on implementation of grassroots burden reduction policies' ⏱️ Total time about 30 minutes (compared to 8-12 days for manual writing, time reduction of 99%)
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.
ResearchProject Proposal Expert v3.0
From vague ideas to logically rigorous application materials, even ordinary technical personnel can complete a 10,000-word argumentation report in 2 hours. Core Features: Eliminate empty language in applications: automatically strip out filler words like 'high-level' and 'significantly improved', use SCQA framework + Pyramid Principle to write quantified, logically rigorous arguments. Accurately identify innovation patterns: automatically analyze project characteristics, match three modes (autonomous originality, integrated innovation, iterative micro-innovation), give compatibility score and recommendation, avoid failure due to mispositioned innovation. Prevent logic gaps in argumentation: exclusive 'five elements + three chapters' structured output method, from project rationale to innovation points tightly linked, master 10,000-word deep report + high-definition technology roadmap. Zero experience required: no idea? Just input a one-sentence project idea (e.g., 'want to make a quantum sensor for gas leak detection'), system automatically completes 6 phases, outputs complete application materials. Usage: Open the dialogue box and directly input your project idea or upload existing materials; the system will guide you through the entire process: information collection → innovation mode selection → brief argumentation generation → full report generation → technology roadmap generation. Each phase has a confirmation mechanism, and you can flexibly exit and iterate. About V3.2: The new V3.2 version integrates five methodologies: SCQA framework, SMART principles, Pyramid Principle, Comparison-Difference-Advantage method, and Three-Dimensional Value method. It has been refined through real-world cases in quantum detection, smart elderly care, energy management, and other fields, locking in the underlying logic of research proposal success—an essential tool for successful project applications! Application scenarios: ✅ National Natural Science Foundation applications ✅ Provincial/municipal science and technology plan projects ✅ Enterprise technology innovation project initiation ✅ Graduate thesis proposal writing ✅ Technology achievement transformation plan design Core advantages: 🎯 Efficiency increase by 10x: from 2-3 weeks to 2-3 hours 📊 Quality professional guarantee: quantified indicators, rigorous logic, prominent innovation points 🔄 Flexible and controllable: each phase can be confirmed, modified, or exited 📈 Validated by real cases: successfully generated multiple 10,000-word deep reports Typical output examples: ✅ 10,000-word deep argumentation report ✅ High-definition technology roadmap ✅ Structured brief argumentation ✅ SCQA diagnostic analysis report ✅ Innovation mode compatibility assessment
Project Closeout Report Pro
8-Step Method + 6D Charts + Natural Language
Description
【Essential for closeout season】Create a high-quality final report in 3 hours—no more rejections! 🔥 Are you also facing these issues? → Closeout deadline approaching, not knowing where to start with years of research materials → After finishing, you realize you missed performance metrics and budget execution details → You want professional charts but don't know how to use complex tools → The generated report has an obvious 'AI smell' and you worry reviewers will notice ✅ This skill solves all these problems at once: 【Highlight 1】8-step structured workflow × Checkpoint mechanism From data collection to final draft, each step has clear guidance and confirmation. Problems are caught as they occur, not at the end. Covers all scenarios: NSFC, provincial/ministerial, and university-level projects. 【Highlight 2】One-click generation of 6 professional chart types Built-in sub-skill generators for word clouds, bar charts, line charts, and more (no extra cost). AI recommends the best chart type and generates in 30 seconds, so reviewers understand your results at a glance. 【Highlight 3】Exclusive 'de-AI-fication' optimization Four-dimensional AI trace detection + three optimization levels (conservative/moderate/aggressive). Replaces empty clichés with more specific, in-depth expressions. Optimized reports are more natural, denser, and more persuasive. 📩 Send feedback/suggestions to 1329806797@qq.com It's not about 'writing' the report, it's about 'getting the whole closeout process right.'
Related Skills
View allThink Tank Report Writer v1.0
🎯 One sentence policy area, produce a directly submittable advisory report in 30 minutes. It's not about 'letting AI write for you,' but packaging 20 years of think tank writing methodology into an engineered pipeline—from topic selection, four-layer penetration, structured drafting to Red-Blue Team quality check, each step goes deeper than you would on your own. ━━━ Who It's For ━━━ ✅ Think tank researchers, government policy researchers, university policy researchers ✅ Writers of internal reference reports, special reports, and policy recommendation reports ✅ Experienced authors who teach advisory report writing to students/teams ━━━ 4 Core Capabilities ━━━ 🎯 Three-Dimensional Topic Scanning Pain point: Topics lack focus, angles are imprecise, recommendations are broad and fragmented. SKILL: Antenna (high-frequency verbs and gaps in policy documents) + Grounding (grassroots pain points) + Side View (horizontal comparison), outputting 3 candidate angles (A1 Problem-Oriented / A2 Comparative Reference / A3 Major Project Proposal each). 🔍 Four-Layer Penetration Analysis Pain point: Reports stay at the surface level, failing to uncover institutional roots, leading to rejection by superiors. SKILL: Phenomenon → Institution → Interests → History, layer by layer penetration. Dig three layers deeper than peers. 📋 Structured Drafting Pain point: Unfamiliar with party-government document formats, confused by three types of internal reference styles. SKILL: A1 Problem-Oriented / A2 Comparative Reference / A3 Major Project Proposal three styles; format 100% aligned with GB/T 9704-2012; out of the box. 🛡️ Red-Blue Team Adversarial Quality Check Pain point: Can't revise your own draft / Obvious AI feel / Don't know where the issues are. SKILL: Switch to reviewer perspective to critique every sentence, graded as P0 (blocks submission) / P1 (recommended fix) / P2 (optional optimization); built-in four-layer de-AI norms (banned words + sentence restructuring + language strategy + structure strategy). ━━━ 📦 One Input, Five Deliverables ━━━ Not just finished writing, but a set of reusable research assets: 1️⃣ Main report docx — 3500-5000 words, party-government document format, directly submittable 2️⃣ Topic angle candidate library — The 2 unused angles already scanned three-dimensionally, ready for next topic 3️⃣ Four-layer penetration analysis framework card — A thinking template transferable to any policy issue 4️⃣ Policy material card library — Data/policy/cases categorized and archived, an asset that grows with use 5️⃣ Red-Blue Team quality check log — Each edit includes [original text + diagnosis + revised text + rationale] ━━━ How It Works ━━━ ⚙️ Five-station pipeline, user confirmation required at each station Station 1: Three-Dimensional Topic Scanning → Station 2: Four-Layer Penetration Analysis → Station 3: Material Dehydration and Transformation → Station 4: Structured Drafting → Station 5: Red-Blue Team Quality Check ⚙️ Dashboard mechanism Each output includes a progress bar (completed / in progress / pending) + a locked parameter list to counter context drift. ⚙️ User confirmation system At the end of each station: ask if you want to proceed. Unsatisfied? You can redo until it's right. ⚙️ Fast track Experienced users with complete information can enter 'fast track' to skip pre-confirmation and go straight to drafting + quality check. ━━━ What We Don't Do (Aesthetic Lockdown) ━━━ ✕ No 'free style' option — the three special report styles have been validated by party-government organs for 20 years; free combining only leads to loss of control ✕ No 'one-click full auto' mode — five-station mandatory confirmation is a quality baseline, not a bug ✕ No delivery without fixing P0 blocking issues — quality relies on system, not luck ━━━ How to Start ━━━ Just say one sentence after opening: 'I want to write an advisory report on county-level elderly care services' 'I want to write an advisory report on financing difficulties of specialized and new enterprises' 'I want to write an advisory report on implementation of grassroots burden reduction policies' ⏱️ Total time about 30 minutes (compared to 8-12 days for manual writing, time reduction of 99%)
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.
ResearchProject Proposal Expert v3.0
From vague ideas to logically rigorous application materials, even ordinary technical personnel can complete a 10,000-word argumentation report in 2 hours. Core Features: Eliminate empty language in applications: automatically strip out filler words like 'high-level' and 'significantly improved', use SCQA framework + Pyramid Principle to write quantified, logically rigorous arguments. Accurately identify innovation patterns: automatically analyze project characteristics, match three modes (autonomous originality, integrated innovation, iterative micro-innovation), give compatibility score and recommendation, avoid failure due to mispositioned innovation. Prevent logic gaps in argumentation: exclusive 'five elements + three chapters' structured output method, from project rationale to innovation points tightly linked, master 10,000-word deep report + high-definition technology roadmap. Zero experience required: no idea? Just input a one-sentence project idea (e.g., 'want to make a quantum sensor for gas leak detection'), system automatically completes 6 phases, outputs complete application materials. Usage: Open the dialogue box and directly input your project idea or upload existing materials; the system will guide you through the entire process: information collection → innovation mode selection → brief argumentation generation → full report generation → technology roadmap generation. Each phase has a confirmation mechanism, and you can flexibly exit and iterate. About V3.2: The new V3.2 version integrates five methodologies: SCQA framework, SMART principles, Pyramid Principle, Comparison-Difference-Advantage method, and Three-Dimensional Value method. It has been refined through real-world cases in quantum detection, smart elderly care, energy management, and other fields, locking in the underlying logic of research proposal success—an essential tool for successful project applications! Application scenarios: ✅ National Natural Science Foundation applications ✅ Provincial/municipal science and technology plan projects ✅ Enterprise technology innovation project initiation ✅ Graduate thesis proposal writing ✅ Technology achievement transformation plan design Core advantages: 🎯 Efficiency increase by 10x: from 2-3 weeks to 2-3 hours 📊 Quality professional guarantee: quantified indicators, rigorous logic, prominent innovation points 🔄 Flexible and controllable: each phase can be confirmed, modified, or exited 📈 Validated by real cases: successfully generated multiple 10,000-word deep reports Typical output examples: ✅ 10,000-word deep argumentation report ✅ High-definition technology roadmap ✅ Structured brief argumentation ✅ SCQA diagnostic analysis report ✅ Innovation mode compatibility assessment
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