PMBOK 8 R&D PM Assistant
One-stop project docs for PMBOK 8 & standards
Description
One-stop software development project management document generation assistant. Built on the PMBOK 8 framework, covering the full lifecycle from project initiation to closure, supporting both predictive (waterfall) and agile methodologies, with 127 standard project document templates built-in, enabling one-click generation of professional project management documents. Core capabilities: • Smart document generation — Project charter, requirements specification, WBS, risk register, test plan, deployment plan, and 127 other document types, automatically categorized by PMBOK 8 performance domains. • Dual methodology — Predictive and agile terminology automatically isolated, with bridging terms added for cross-methodology references, ensuring professional consistency. • Three standard systems — Integrated with China's CSPM (GB/T 41831/41246), e-government (国办发57号/等保/密评), and Hong Kong DPO standard systems, with automatic keyword detection and adaptation. • Trilingual output — Simplified Chinese, Traditional Chinese (Hong Kong usage), and English, supporting parallel multi-language generation. • Flexible configuration — Three orthogonal dimensions: proficiency (beginner/expert), richness (simple/standard/professional), and output language. • Project folder — Automatically creates PMBOK 8 focus area folder structure, documents auto-sorted, maintaining a project document master index. • Smart sensing — Paste meeting minutes, emails, logs, automatically identify project events and link to corresponding documents. • Template learning — Upload your templates, the Skill learns the structure and generates documents in your format. Applicable scenarios: Software development project managers, PMOs, technical leads, agile coaches, and teams needing standardized project management documents. Whether you use PMBOK, CSPM, or DPO systems, quickly generate compliant project documents.
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CMMI V2.0 Document Assistant
One-stop CMMI V2.0 document system builder. Covers all models (DEV/Services/People/Supplier/Security) ML2-ML5, with practice areas (PA) as the main axis. Each PA generates three-level documents: process description, template, and record. Supports bilingual output in Chinese and English. Core capabilities: - Intelligent document generation — 25+ PA × three-level documents, automatically categorized according to CMMI's four category domains (Execution, Management, Support, Improvement), with built-in complete structure definitions - Four intents — Template generation, material to document, intelligent update, and system health check. Automatically recognizes user intent and confirms before execution - System health check — Cross-PA coverage calculation, gap grading analysis, phased action plan, and assessment readiness evaluation - Bilingual output — Simplified Chinese and English freely combinable; CMMI standard abbreviations remain in English - Status tracking — Maintain project context status matrix, gap register, and document system general catalog - Project folder — Automatically create folder structure by CMMI category domains; documents are automatically placed - Intelligent awareness — Paste meeting minutes, logs, or emails; automatically recognizes 10 types of project events and associates corresponding PA documents - Version verification — Automatically detects and corrects CMMI version misnomers (e.g., V3→V2.0) - Agile adaptation — Supports CMMI practice adaptation in agile development environments Applicable scenarios: CMMI assessment preparation teams, EPG/process improvement groups, QA managers, project managers, and organizations that need to build a CMMI compliant document system. Whether the goal is ML2 entry-level or ML5 optimization-level, this assistant can quickly generate a process document system that meets CMMI V2.0 standards.
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.
Bid Proposal Writer V4
Automatically draft the technical section of bid proposals against the scoring criteria. Runs a four-stage workflow covering in-depth tender document analysis, scoring strategy analysis, technical proposal drafting, quality checks, and document output. Supports IT projects including software development, system integration, IT operations and maintenance, consulting and design, and cloud services. Outputs technical proposal documents in Markdown + Word. Strictly prohibits simulating or fabricating scoring criteria or inventing bidder data; placeholders are used in all cases.
PMBOK 8 R&D PM Assistant
One-stop project docs for PMBOK 8 & standards
Description
One-stop software development project management document generation assistant. Built on the PMBOK 8 framework, covering the full lifecycle from project initiation to closure, supporting both predictive (waterfall) and agile methodologies, with 127 standard project document templates built-in, enabling one-click generation of professional project management documents. Core capabilities: • Smart document generation — Project charter, requirements specification, WBS, risk register, test plan, deployment plan, and 127 other document types, automatically categorized by PMBOK 8 performance domains. • Dual methodology — Predictive and agile terminology automatically isolated, with bridging terms added for cross-methodology references, ensuring professional consistency. • Three standard systems — Integrated with China's CSPM (GB/T 41831/41246), e-government (国办发57号/等保/密评), and Hong Kong DPO standard systems, with automatic keyword detection and adaptation. • Trilingual output — Simplified Chinese, Traditional Chinese (Hong Kong usage), and English, supporting parallel multi-language generation. • Flexible configuration — Three orthogonal dimensions: proficiency (beginner/expert), richness (simple/standard/professional), and output language. • Project folder — Automatically creates PMBOK 8 focus area folder structure, documents auto-sorted, maintaining a project document master index. • Smart sensing — Paste meeting minutes, emails, logs, automatically identify project events and link to corresponding documents. • Template learning — Upload your templates, the Skill learns the structure and generates documents in your format. Applicable scenarios: Software development project managers, PMOs, technical leads, agile coaches, and teams needing standardized project management documents. Whether you use PMBOK, CSPM, or DPO systems, quickly generate compliant project documents.
Related Skills
View allCMMI V2.0 Document Assistant
One-stop CMMI V2.0 document system builder. Covers all models (DEV/Services/People/Supplier/Security) ML2-ML5, with practice areas (PA) as the main axis. Each PA generates three-level documents: process description, template, and record. Supports bilingual output in Chinese and English. Core capabilities: - Intelligent document generation — 25+ PA × three-level documents, automatically categorized according to CMMI's four category domains (Execution, Management, Support, Improvement), with built-in complete structure definitions - Four intents — Template generation, material to document, intelligent update, and system health check. Automatically recognizes user intent and confirms before execution - System health check — Cross-PA coverage calculation, gap grading analysis, phased action plan, and assessment readiness evaluation - Bilingual output — Simplified Chinese and English freely combinable; CMMI standard abbreviations remain in English - Status tracking — Maintain project context status matrix, gap register, and document system general catalog - Project folder — Automatically create folder structure by CMMI category domains; documents are automatically placed - Intelligent awareness — Paste meeting minutes, logs, or emails; automatically recognizes 10 types of project events and associates corresponding PA documents - Version verification — Automatically detects and corrects CMMI version misnomers (e.g., V3→V2.0) - Agile adaptation — Supports CMMI practice adaptation in agile development environments Applicable scenarios: CMMI assessment preparation teams, EPG/process improvement groups, QA managers, project managers, and organizations that need to build a CMMI compliant document system. Whether the goal is ML2 entry-level or ML5 optimization-level, this assistant can quickly generate a process document system that meets CMMI V2.0 standards.
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.
Bid Proposal Writer V4
Automatically draft the technical section of bid proposals against the scoring criteria. Runs a four-stage workflow covering in-depth tender document analysis, scoring strategy analysis, technical proposal drafting, quality checks, and document output. Supports IT projects including software development, system integration, IT operations and maintenance, consulting and design, and cloud services. Outputs technical proposal documents in Markdown + Word. Strictly prohibits simulating or fabricating scoring criteria or inventing bidder data; placeholders are used in all cases.
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