Report Deep Audit
Deep-check data, logic, and consistency
Description
In-depth audit of reports and proposals. Use when a user uploads a report (Word, PDF, or PPT) and asks to “review it,” “audit it in depth,” “find the problems,” “tell me whether this report is good enough,” “can it be submitted,” “check the final draft,” or “evaluate and review the report.” Treat the report as a formal deliverable intended for a client or executive, and conduct a nine-dimension review with a two-axis determination (quality score × revision type). Systematically extract all data assets, including embedded charts. Provide a decision-oriented review in the first round, then expand it into the full version after confirmation.
Related Skills
View all
Project Closeout Report Pro
【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.'
WriteAccident Root Cause & Actions
Do you find yourself repeatedly asking these questions in safety management? An accident analysis report runs dozens of pages, yet its conclusions still stop at “employee violated procedures” or “weak safety awareness,” leaving the real cause undiscovered? You issue a long list of corrective actions, but they amount to vague statements like “strengthen training” and “improve systems”—with no clear path to implementation, while similar accidents continue to happen? The accident investigation report contains extensive details, but you do not know how to organize them into a clear chain of causation that lets management see the root problem at a glance? When facing a regulatory or group review, you need a rigorous, layered analysis, but the tools available are either too superficial or too theoretical to reflect real-world conditions? You want to use external accident cases for internal safety awareness, but worry that exposing company names could create unnecessary public-opinion risks? Effective safety management is not about assigning “blame” after an incident; it is about identifying causes in advance. Only by uncovering the problems embedded deep within the organization can corrective actions truly take hold. This Skill is an intelligent assistant that provides in-depth analysis and improvement recommendations like an experienced safety expert. What is it? A professional tool that analyzes the root causes of an accident and generates actionable recommendations based on the original accident investigation report. It avoids generalities and stays faithful to the source material you provide, accurately extracting key information, reconstructing what happened, and tracing the causes layer by layer like a detective until it reaches the underlying systemic defects. How does it work? Reach the root cause in three steps Provide the accident investigation report — Upload or paste the complete investigation report, internal notice, or detailed description of the accident; Automatic in-depth analysis — The tool intelligently extracts key information from the report, including the timeline, actions of involved personnel, equipment status, and descriptions of management systems. It objectively reconstructs the accident in detail and ensures that every analysis remains faithful to the source material without subjective assumptions; Get layered diagnoses and improvement prescriptions — You will receive a clearly structured analysis report that can be put into practice directly. Why can its framework “peel back the layers”? Unlike traditional accident analysis, this tool clearly divides causes into three levels, making problems easier to see, address, and fix: Level 1: Direct causes — Identifies the specific actions or conditions that led to the accident, such as “an employee failed to close a valve according to procedure” or “a safety interlock on a piece of equipment failed.” These are the immediate triggers of the accident and the easiest facts to observe. Level 2: Contributing causes — Reveals systemic problems in company management, such as gaps in procedures, insufficient training, inadequate supervision, or incomplete maintenance. For example: “The operating procedure for this position did not specify the emergency shutdown process” or “The equipment had not received a periodic inspection in the past year.” These are the conditions that allowed the direct causes to arise. Level 3: Root causes — Further uncovers deep defects in the company’s safety management system or safety culture, such as “Long-term underinvestment in safety left aging equipment without timely replacement,” “Management prioritized production over safety, with assessment metrics disconnected from safety performance,” or “Safety responsibilities weakened at each level, leaving frontline employees afraid to report hazards.” These are the areas that truly require fundamental corrective action. All analysis remains strictly focused on the company’s internal situation, and company names are anonymized to ensure safe, objective discussion suitable for internal analysis and external communication. Why are the improvement recommendations actionable? For every identified cause, the tool generates specific, executable measures that can be implemented—not empty phrases like “strengthen management.” For example: Identified cause Corresponding improvement recommendation (example) Direct cause: The valve was not closed as required Revise the operating procedure for the position to add a step requiring two-person confirmation and signatures after the valve is closed; install a position sensor on the valve and connect it to the central control system for alarm notifications Contributing cause: No equipment inspection was conducted in the past year Create an annual inspection plan for this type of equipment, specifying the inspection cycle and responsible person; include inspection results in the equipment records, with automatic reminders for overdue inspections Root cause: Insufficient safety investment and aging equipment Create a dedicated budget for safety equipment upgrades in the annual budget; include equipment safety status in the workshop director’s monthly performance evaluation, with a weighting of no less than 15% Every recommendation specifies “who will do what, how, and by when,” avoiding vague language and helping companies effectively prevent similar accidents while continuously improving workplace safety. Broad, practical use cases Accident reviews and internal analysis meetings — Provide objective, in-depth analysis materials and guide discussions from “assigning blame” toward “improvement”; Corrective action planning — Generate a corrective-action task list directly from the analysis conclusions, with clear ownership and specific measures; Submitting accident analysis reports to regulators or group headquarters — Provide a rigorous, clearly structured professional report; Developing safety training materials — Turn your company’s or industry peers’ accident cases into real and persuasive teaching materials; Safety management system reviews and upgrades — Extract systemic issues from individual accidents and drive broader improvements to the management system. More than an analysis report Ultimately, you will receive a complete, ready-to-use deliverables package, including: Accident reconstruction summary: An objective timeline based on the source material; Three-level cause analysis table: A clear side-by-side view of direct, contributing, and root causes; Targeted improvement action list: Every measure corresponds to a specific cause and defines the implementation direction and acceptance criteria; Analysis explanation document: An explanation of the analytical logic and reasoning process, making it easier to explain and advance the findings with your team. All content anonymizes company names to ensure safety and practical use. So, the next time you face an accident report and are no longer satisfied with shallow, incident-by-incident conclusions, do not rely on intuition or generic templates. Give it a real report, and it will return a deep, actionable plan for systematic improvement. Uncover the root cause to truly prevent further loss—and give every “why” an answer.
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.
Report Deep Audit
Deep-check data, logic, and consistency
Description
In-depth audit of reports and proposals. Use when a user uploads a report (Word, PDF, or PPT) and asks to “review it,” “audit it in depth,” “find the problems,” “tell me whether this report is good enough,” “can it be submitted,” “check the final draft,” or “evaluate and review the report.” Treat the report as a formal deliverable intended for a client or executive, and conduct a nine-dimension review with a two-axis determination (quality score × revision type). Systematically extract all data assets, including embedded charts. Provide a decision-oriented review in the first round, then expand it into the full version after confirmation.
Related Skills
View allProject Closeout Report Pro
【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.'
WriteAccident Root Cause & Actions
Do you find yourself repeatedly asking these questions in safety management? An accident analysis report runs dozens of pages, yet its conclusions still stop at “employee violated procedures” or “weak safety awareness,” leaving the real cause undiscovered? You issue a long list of corrective actions, but they amount to vague statements like “strengthen training” and “improve systems”—with no clear path to implementation, while similar accidents continue to happen? The accident investigation report contains extensive details, but you do not know how to organize them into a clear chain of causation that lets management see the root problem at a glance? When facing a regulatory or group review, you need a rigorous, layered analysis, but the tools available are either too superficial or too theoretical to reflect real-world conditions? You want to use external accident cases for internal safety awareness, but worry that exposing company names could create unnecessary public-opinion risks? Effective safety management is not about assigning “blame” after an incident; it is about identifying causes in advance. Only by uncovering the problems embedded deep within the organization can corrective actions truly take hold. This Skill is an intelligent assistant that provides in-depth analysis and improvement recommendations like an experienced safety expert. What is it? A professional tool that analyzes the root causes of an accident and generates actionable recommendations based on the original accident investigation report. It avoids generalities and stays faithful to the source material you provide, accurately extracting key information, reconstructing what happened, and tracing the causes layer by layer like a detective until it reaches the underlying systemic defects. How does it work? Reach the root cause in three steps Provide the accident investigation report — Upload or paste the complete investigation report, internal notice, or detailed description of the accident; Automatic in-depth analysis — The tool intelligently extracts key information from the report, including the timeline, actions of involved personnel, equipment status, and descriptions of management systems. It objectively reconstructs the accident in detail and ensures that every analysis remains faithful to the source material without subjective assumptions; Get layered diagnoses and improvement prescriptions — You will receive a clearly structured analysis report that can be put into practice directly. Why can its framework “peel back the layers”? Unlike traditional accident analysis, this tool clearly divides causes into three levels, making problems easier to see, address, and fix: Level 1: Direct causes — Identifies the specific actions or conditions that led to the accident, such as “an employee failed to close a valve according to procedure” or “a safety interlock on a piece of equipment failed.” These are the immediate triggers of the accident and the easiest facts to observe. Level 2: Contributing causes — Reveals systemic problems in company management, such as gaps in procedures, insufficient training, inadequate supervision, or incomplete maintenance. For example: “The operating procedure for this position did not specify the emergency shutdown process” or “The equipment had not received a periodic inspection in the past year.” These are the conditions that allowed the direct causes to arise. Level 3: Root causes — Further uncovers deep defects in the company’s safety management system or safety culture, such as “Long-term underinvestment in safety left aging equipment without timely replacement,” “Management prioritized production over safety, with assessment metrics disconnected from safety performance,” or “Safety responsibilities weakened at each level, leaving frontline employees afraid to report hazards.” These are the areas that truly require fundamental corrective action. All analysis remains strictly focused on the company’s internal situation, and company names are anonymized to ensure safe, objective discussion suitable for internal analysis and external communication. Why are the improvement recommendations actionable? For every identified cause, the tool generates specific, executable measures that can be implemented—not empty phrases like “strengthen management.” For example: Identified cause Corresponding improvement recommendation (example) Direct cause: The valve was not closed as required Revise the operating procedure for the position to add a step requiring two-person confirmation and signatures after the valve is closed; install a position sensor on the valve and connect it to the central control system for alarm notifications Contributing cause: No equipment inspection was conducted in the past year Create an annual inspection plan for this type of equipment, specifying the inspection cycle and responsible person; include inspection results in the equipment records, with automatic reminders for overdue inspections Root cause: Insufficient safety investment and aging equipment Create a dedicated budget for safety equipment upgrades in the annual budget; include equipment safety status in the workshop director’s monthly performance evaluation, with a weighting of no less than 15% Every recommendation specifies “who will do what, how, and by when,” avoiding vague language and helping companies effectively prevent similar accidents while continuously improving workplace safety. Broad, practical use cases Accident reviews and internal analysis meetings — Provide objective, in-depth analysis materials and guide discussions from “assigning blame” toward “improvement”; Corrective action planning — Generate a corrective-action task list directly from the analysis conclusions, with clear ownership and specific measures; Submitting accident analysis reports to regulators or group headquarters — Provide a rigorous, clearly structured professional report; Developing safety training materials — Turn your company’s or industry peers’ accident cases into real and persuasive teaching materials; Safety management system reviews and upgrades — Extract systemic issues from individual accidents and drive broader improvements to the management system. More than an analysis report Ultimately, you will receive a complete, ready-to-use deliverables package, including: Accident reconstruction summary: An objective timeline based on the source material; Three-level cause analysis table: A clear side-by-side view of direct, contributing, and root causes; Targeted improvement action list: Every measure corresponds to a specific cause and defines the implementation direction and acceptance criteria; Analysis explanation document: An explanation of the analytical logic and reasoning process, making it easier to explain and advance the findings with your team. All content anonymizes company names to ensure safety and practical use. So, the next time you face an accident report and are no longer satisfied with shallow, incident-by-incident conclusions, do not rely on intuition or generic templates. Give it a real report, and it will return a deep, actionable plan for systematic improvement. Uncover the root cause to truly prevent further loss—and give every “why” an answer.
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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