docs(use-cases): P0 English rewrite

docs/03-use-cases/01-general/06-data-analysis-agent.md

@@ -169,5 +169,5 @@ keywords: [数据分析, 报告生成, 可视化, Excel, 财务报告]
 | 格式一致性 | 易出错 | 高 | 高 |
 
 :::tip 使用建议
-何洁这类周期性报告最适合先固化模板和指标口径。模板稳定后，每月主要检查异常解释和管理建议，不需要反复调整版式。
+这类周期性报告最适合先固化模板和指标口径。模板稳定后，每月主要检查异常解释和管理建议，不需要反复调整版式。
 :::

i18n/en/docusaurus-plugin-content-docs/current/03-use-cases/01-general/01-document-writing.md

@@ -1,20 +1,26 @@
 ---
 title: Document Writing
-description: Use the AI Copywriter agent to efficiently complete various writing tasks from outline to final draft, including project reports and proposal documents.
+description: Use the AI Copywriter agent to organize ideas, generate outlines, draft project reports and proposal documents.
 keywords: [Document Writing, AI Copywriter, Reports, Writing Assistant, Content Creation]
 ---
 
 # Document Writing
 
-## Scenario Description
+## Real Workflow
 
-You need to write a project report but don't know where to start facing a blank page. Or you already have ideas, but organizing them into a well-structured, professionally expressed document takes a lot of time.
+This scenario doesn't work by "letting AI write a report from scratch"—it requires the user to already have a batch of scattered but real materials that need to be organized into deliverable documents.
 
-The AI Copywriter agent can help you from scratch: first organize ideas to generate an outline, then gradually expand it into a complete draft, and finally make precise modifications based on your feedback. The entire process is like collaborating with an experienced writing partner.
+| Dimension | Real Situation |
+|-----------|----------------|
+| Trigger Point | Project review, client report, quarterly summary, proposal review requiring formal materials |
+| Existing Materials | Project background, key data, meeting minutes, chat conclusions, existing PPTs or spreadsheets |
+| Pain Point | Information scattered, structure undecided, tone and audience unclear, repeated format changes time-consuming |
+| DesireCore Intervention | AI Copywriter first organizes outline, then generates drafts by chapter; data or charts can be delegated to Data Analyst when needed |
+| Acceptance Result | Person in charge receives a reviewable document draft, then supplements facts, sets conclusions, adjusts tone |
 
 ## Recommended Agent
 
-**AI Copywriter** -- A knowledge-based agent focused on content creation and copywriting, excelling in brand copy, marketing planning, and multi-style adaptation.
+**AI Copywriter** — Suitable for reports, proposals, announcements, marketing copy and other text tasks; generates drafts according to your specified audience, tone and template.
 
 ## Complete Conversation Example
 
@@ -70,17 +76,25 @@ AI Copywriter: Adjusted to a more formal business style and added quantitative m
 
 ## Key Steps
 
-1. **Clarify Requirements** -- Tell the agent the document type, purpose, and target audience
-2. **Generate Outline** -- The agent generates a structured outline based on your information
-3. **Write Draft** -- After confirming the outline, expand each chapter into complete content
-4. **Review and Revise** -- You provide revision suggestions, and the agent precisely adjusts style, wording, and data
+1. **Define Deliverable Audience** — First clarify who the document is for: client, boss, review committee, archiving system; different audiences mean different structure and tone
+2. **Organize Fact Package** — List project scope, deliverables, timeline, budget, key data, outstanding issues and lessons learned
+3. **Review Structure Before Writing** — Confirm chapters cover background, completed work, result comparison, issues and next steps before expanding each section
+4. **Complete Evidence Chain** — For each conclusion, add data, screenshots, links or sources to avoid just having nice words
+5. **Generate Versions by Use Case** — The same materials can generate formal reports, summary briefs, email versions or archive versions
 
 ## Final Deliverable
 
-A well-structured, professionally expressed project summary report with quantitative data support and clear logical flow, ready for presentation or archiving.
+A complete, well-structured document draft with traceable factual basis, chapter logic and reusable versions. You can continue having the AI Copywriter supplement data, adjust tone, compress length or create presentation versions.
+
+## DesireCore Capabilities Used
+
+- **Super Document**: View AI modifications in Diff format, accept, reject or continue editing each change individually
+- **Natural Language Teaching**: Teach report templates, word prohibitions, writing styles to the AI Copywriter for future reuse
+- **Multi-Agent Collaboration**: Data, charts, legal clauses etc. can be delegated to corresponding agents first, then integrated by AI Copywriter
 
 :::tip Best Practices
-- Provide sufficient background information (data, timelines, key stakeholders) in the first communication for more accurate content generation
-- Make good use of "Super Document Mode" which can coordinate multiple agents in one document, such as having the Data Analyst provide chart data, then having the AI Copywriter integrate it into the report
-- If you're not satisfied with a paragraph, point out specific issues (e.g., "tone too casual", "lacks data support") rather than vaguely saying "make it better"
-:::
+- Provide background information, data, timeline and key people in your first communication; minimize having the agent fill in assumptions
+- When dissatisfied with a paragraph, point out specific issues like "tone too casual", "lacks data support", "this section doesn't match facts"
+- For charts, data conclusions or contract clauses, let corresponding agents process them first in Super Document mode, then have AI Copywriter integrate into the report
+- Project summary documents should not just list "what was done"—also include whether scope was completed, timeline/budget deviations, outstanding issues and lessons learned
+:::

i18n/en/docusaurus-plugin-content-docs/current/03-use-cases/01-general/02-data-analysis.md

@@ -1,24 +1,30 @@
 ---
 title: Data Analysis
-description: Use the Data Analyst agent to quickly analyze sales data, user behavior, etc., and obtain visual reports and trend insights.
+description: Use the Data Analyst agent to clean spreadsheets, calculate metrics, generate charts and organize analysis conclusions.
 keywords: [Data Analysis, Reports, Visualization, Trend Prediction, Data Analyst]
 ---
 
 # Data Analysis
 
-## Scenario Description
+## Real Workflow
 
-You have a sales data spreadsheet, and your boss wants trend analysis and next quarter's forecast by this afternoon. Manually organizing data, creating charts, and writing analysis conclusions would take at least half a day.
+This scenario usually happens when "data exists but explanation is missing." Users don't want a vague analysis—they want a specific business question answered.
 
-The Data Analyst agent can complete this work in minutes: automatically identifying data formats, cleaning outliers, generating statistical summaries, creating visual charts, and providing actionable analysis conclusions.
+| Dimension | Real Situation |
+|-----------|----------------|
+| Trigger Point | Weekly meeting, business review, abnormal metrics review, boss suddenly asks about a business fluctuation |
+| Existing Materials | CSV/Excel data, metric definitions, target values, historical comparison periods, business context |
+| Pain Point | Data cleaning, metric definitions, chart selection and anomaly attribution all pile together, very time-pressured |
+| DesireCore Intervention | Data Analyst first does data overview and definition confirmation, then generates charts, comparisons and preliminary explanations by question |
+| Acceptance Result | User gets metric tables, charts and conclusion hypotheses that support discussion, then decides which ones go into the report |
 
 ## Recommended Agent
 
-**Data Analyst** -- Specializes in data cleaning, statistical analysis, trend prediction, and visual report generation, supporting CSV, Excel, JSON, and other data formats.
+**Data Analyst** — Suitable for data cleaning, statistical analysis, trend comparison, anomaly detection and visual report generation; supports CSV, Excel, JSON and other common data formats.
 
-## Teaching First: Setting Your Business Metrics
+## Teaching First: Master Your Business Metrics
 
-> Every company calculates GMV, conversion rates, and other metrics differently. Teach your definitions once, and every future analysis will use the correct standards -- no more "the numbers don't match" moments.
+> Every company calculates GMV, conversion rates and other metrics differently. Teach your definitions once, and every future analysis will use the correct standards—no more "the numbers don't match" moments.
 
 ### Teaching Rules
 
@@ -105,18 +111,20 @@ Data Analyst: West China deep dive analysis results:
 
 ## Key Steps
 
-1. **Upload Data** -- Upload CSV, Excel, or JSON files to the agent
-2. **Describe Analysis Needs** -- Explain what you want to understand (trends, comparisons, predictions, etc.)
-3. **Get Analysis Results** -- The agent automatically generates statistical summaries, charts, and insights
-4. **Deep Dive** -- Ask follow-up questions about discovered issues for deeper analysis
+1. **Define Business Question** — First clarify what question needs answering, e.g., "which region dragged down sales targets" rather than just "analyze data"
+2. **Confirm Metric Definitions** — Specify time range, metric definitions, refund/cancellation handling and target value sources
+3. **Data Health Check** — First check column names, missing values, duplicates, outliers and category naming consistency
+4. **Explore and Compare** — Compare by time, region, channel, product, demographic and other dimensions to find major differences
+5. **Form Verifiable Conclusions** — Write conclusions as "phenomenon + data evidence + possible causes + next verification steps", avoid just giving subjective judgments
 
 ## Final Deliverable
 
-A complete analysis report with key metrics, regional comparisons, trend charts, anomaly detection, and improvement recommendations, ready for team presentations.
+An analysis report containing key metrics, data quality notes, comparison dimensions, trend charts, anomaly explanations and next-step verification suggestions.
 
 :::tip Best Practices
 - Ensure clear column names before uploading (e.g., "Sales Amount" instead of "col_1") so the agent can better understand data meaning
 - The more specific your analysis requirements, the more precise the results. "Analyze sales trends" is less effective than "Compare Q3 and Q4 growth rates by region, identifying the fastest and slowest growing regions"
 - If the data volume is large, have the agent do a data overview first, then dive deeper into directions of interest
-- **Batch analyze multi-department data**: When you need to review data across departments or product categories on Monday morning, send everything to the Data Analyst at once -- it will analyze each dataset in parallel, all using the same metric standards and report template you taught
-:::
+- When batch analyzing multi-department data, first confirm all spreadsheets use the same metric definitions and time range, then have the agent process in parallel
+- Don't skip data health checks. Many "business anomalies" actually come from empty values, duplicate orders, definition changes or export scope inconsistencies
+:::

i18n/en/docusaurus-plugin-content-docs/current/03-use-cases/01-general/03-email-management.md

@@ -1,16 +1,22 @@
 ---
 title: Email Management
-description: Use the AI Assistant to intelligently classify emails, draft replies, and extract key information for efficient daily email processing.
+description: Use the email assistant to classify emails, extract key information, organize to-dos and draft replies.
 keywords: [Email Management, Email Classification, Email Replies, Efficiency, AI Assistant]
 ---
 
 # Email Management
 
-## Scenario Description
+## Real Workflow
 
-You open your inbox on Monday morning to find over 50 unread emails. There are clients催促 delivery, colleagues asking about progress, administrative notices, and a pile of promotional emails. Reading and replying to each one would take at least two hours.
+This scenario isn't about "letting AI send emails for you"—it's about transforming your inbox from a pile of unread messages into a manageable work queue.
 
-The AI Assistant can help you process these emails quickly: classifying by importance, extracting key information from each email, and drafting reply content, allowing you to focus on what truly requires your personal attention.
+| Dimension | Real Situation |
+|-----------|----------------|
+| Trigger Point | After vacation, Monday morning, before/after project launch—emails pile up |
+| Existing Materials | Email body, sender identity, historical communication context, attachments or contract context |
+| Pain Point | Important emails mixed with notifications; to-dos, deadlines and responsible people unclear |
+| DesireCore Intervention | First classify and sort, then extract summaries, to-dos and suggested replies; sensitive emails can have multiple reply versions generated |
+| Acceptance Result | User sees priority list and reply drafts, handles client, deadline and contract emails first |
 
 ## Complete Conversation Example
 
@@ -68,17 +74,25 @@ AI Assistant: Revised, please confirm:
 
 ## Key Steps
 
-1. **Paste Email Content** -- Provide the email body to the agent
-2. **Smart Classification** -- The agent automatically identifies email importance and type
-3. **Extract Key Information** -- Summarize email highlights and flag items requiring your attention
-4. **Draft Reply** -- Generate reply drafts based on email content and your needs
+1. **Merge Context** — First merge emails from the same client or project into threads, avoid only seeing the last email
+2. **First-Round Triage** — Classify into "handle immediately / handle today / delegate / wait for reply / archive for reference"
+3. **Extract Commitments** — For each action email, extract task, responsible person, deadline, source email and dependencies
+4. **Generate Reply Drafts** — Create drafts with different tones for clients, internal colleagues, vendors etc.
+5. **Build Follow-Up Queue** — Separately list emails waiting for client reply, internal confirmation or needing reminders
 
 ## Final Deliverable
 
-Each email has clear classification labels, key information summaries, and ready-to-use reply drafts, cutting email processing time by more than half.
+Each email gets classification labels, key information summary, to-dos, reply drafts and follow-up status. You can handle urgent client matters first, then batch process internal collaboration and notification emails.
+
+## DesireCore Capabilities Used
+
+- **Email Center**: Gmail, Outlook, IMAP unified management; view context by conversation thread
+- **Natural Language Teaching**: Teach the agent your client reply style, escalation rules and prohibited expressions
+- **Security Confirmation**: Client commitments, contracts, complaints and other important emails retain manual confirmation before sending
 
 :::tip Best Practices
-- When processing in bulk, you can paste multiple emails at once, and the agent will sort them by importance
-- Tell the agent your reply habits (e.g., "I usually use a formal tone"), and it will remember and apply them to subsequent replies
+- When processing in bulk, you can paste multiple emails at once—the agent will sort them by importance
+- Tell the agent your reply habits (e.g., "more formal for client emails, more concise for internal emails"), and subsequent drafts will better match your style
 - For emails requiring careful wording (e.g., customer complaints, contract negotiations), have the agent provide multiple versions for you to choose from
-:::
+- Important to-dos should retain source email links or original text snippets, so you won't lose context when tracing back for accountability
+:::