email-analytics

# Email Analytics Get a data‑driven view of your email life. This skill scans your inbox and sent folder over a time period, crunches the numbers, and presents a formatted analytics dashboard — volume by day, top senders, response patterns, busiest hours, flagged backlogs, and unread trends. Use it to understand your communication load and identify where your email time goes. ## When to Use - "Analyze my email patterns this month" - "How many emails did I get last week?" - "Who sends me the most email?" - "Show me my email volume trends" - "Give me inbox statistics for the last 30 days" - "What does my email workload look like?" ## Instructions ### Step 1: Identify the User ``` workiq-ask ( question: "What is my profile information including display name and email address?" ) ``` Extract **displayName** and **mail** for report personalization. ### Step 2: Retrieve Received Emails Pull all received emails across the analysis period: ``` workiq-ask ( question: "List all emails I received in the last <time period>. For each email include the sender name and email, subject, received date and time, read/unread status, importance level, whether it has attachments, and flag status." ) ``` For longer periods, run multiple queries to capture the full window: - `"List all emails I received this week with sender, subject, date, read status, importance, attachments, and flag status"` - `"List all emails I received last week with sender, subject, date, read status, importance, attachments, and flag status"` - etc. ### Step 3: Retrieve Sent Emails Pull all sent emails for response analysis: ``` workiq-ask ( question: "List all emails I sent in the last <time period>. For each email include the recipients, subject, sent date and time, and whether it has attachments." ) ``` Collect for each message (received and sent): - **From / To** — sender and recipient addresses - **ReceivedDateTime** — timestamp for volume trends - **IsRead** — read vs. unread status - **Importance** — high/normal/low - **HasAttachments** — attachment tracking - **Flag status** — flagged items count - **Subject** — for thread grouping ### Step 4: Compute Analytics Aggregate the data into the following metrics: **Volume Metrics:** - Total received, total sent - Daily average received / sent - Ratio of received to sent **Temporal Patterns:** - Volume by day of week (Mon–Sun) - Peak hours (morning, afternoon, evening) - Busiest single day **People Metrics:** - Top 10 senders by volume - Top 10 recipients you email most - Emails from direct manager **Status Metrics:** - Unread count and percentage - Flagged count - High importance count - Emails with attachments ### Step 5: Present the Analytics Dashboard ``` 📊 EMAIL ANALYTICS — {displayName} ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📅 Period: {start date} → {end date} ({N} days) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📬 VOLUME OVERVIEW ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📥 Received: {total received} ({daily avg}/day) 📤 Sent: {total sent} ({daily avg}/day) 📈 Ratio: {received:sent ratio} 📬 Unread: {unread count} ({unread %}%) 🚩 Flagged: {flagged count} ⚡ High Priority: {high importance count} 📅 VOLUME BY DAY OF WEEK ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Mon │ ████████████████████░░░░░ 82 Tue │ ███████████████████████░░ 94 ← busiest Wed │ ██████████████████░░░░░░░ 73 Thu │ █████████████████████░░░░ 86 Fri │ ██████████████░░░░░░░░░░░ 58 Sat │ ███░░░░░░░░░░░░░░░░░░░░░ 12 Sun │ ██░░░░░░░░░░░░░░░░░░░░░░ 8 👤 TOP SENDERS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ #1 Firstname1 Lastname1 │ 34 emails │ ████████████████ #2 notifications@jira │ 28 emails │ █████████████ #3 Firstname2 Lastname2 │ 22 emails │ ██████████ #4 Firstname3 Lastname3 │ 18 emails │ ████████ #5 build-alerts@ci │ 15 emails │ ███████ #6 Firstname4 Lastname4 │ 14 emails │ ██████ #7 calendar@outlook │ 12 emails │ █████ #8 Firstname5 Lastname5 │ 10 emails │ ████ #9 newsletter@company │ 9 emails │ ████ #10 help-desk@contoso │ 7 emails │ ███ 👤 TOP RECIPIENTS (your sent mail) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ #1 Firstname1 Lastname1 │ 19 emails #2 Firstname2 Lastname2 │ 14 emails #3 Manager: Firstname6 Lastname6 │ 11 emails #4 Firstname3 Lastname3 │ 9 emails #5 Team DL │ 8 emails 📎 ATTACHMENT STATS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📎 Emails with attachments: {count} ({percentage}%) 📊 Most common types: PDF, XLSX, DOCX 🔍 INSIGHTS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💡 Tuesday is your busiest email day — consider blocking focus time. 💡 {unread count} unread emails — consider triaging your inbox. 💡 {percentage}% of received email is from automated systems. 💡 You send {ratio} emails for every {N} received. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ``` ## Output Format A formatted analytics dashboard with bar charts for volume trends, ranked sender/recipient tables, attachment statistics, and actionable insights. Bar charts use Unicode block characters for visual representation. ## Parameters | Parameter | Required | Default | Description | |-----------|----------|---------|-------------| | Time period | No | Last 7 days | Analysis window (e.g., "this month", "last 30 days", "this quarter") | | Include sent | No | true | Whether to analyze outgoing emails too | | Detail level | No | full | `summary` (volume only) or `full` (all sections) | | Show insights | No | true | Include AI‑generated insights and recommendations | ## Required MCP Tools | MCP Server | Tool | Purpose | |---|---|---| | workiq (Local WorkIQ CLI) | `ask` | User identity, email retrieval (received and sent), and message metadata for analytics | ## Tips - Run weekly for a quick health check on your email workload, or monthly for trend spotting. - High automated‑email percentage? Consider unsubscribing or filtering newsletter noise. - Compare week‑over‑week by running twice with different date ranges. - The insights section auto‑detects patterns like automated senders, unread backlogs, and busiest days to give you actionable advice. - If email peaks align with meeting‑heavy days, you may need more focus time. ## Examples **Last 7 days at a glance** > "Analyze my email patterns for the last week" Returns a full dashboard covering the past 7 days — total received and sent, top senders, busiest day, unread count, and key insights like automated-email percentage. --- **Monthly deep-dive** > "Give me inbox statistics for March" Runs a 31-day analysis, identifying volume trends by day of week, ranking your top 10 senders, and flagging any growing unread backlog. Useful for end-of-month reporting or planning the next sprint. --- **Quick sender check** > "Who sends me the most email this quarter?" Focuses the output on the Top Senders table. Even when requesting a narrow slice, the full dashboard is generated — scroll to the **TOP SENDERS** section or ask for `detail level: summary` to limit output to volume and sender rankings only. ## Error Handling **No emails found for the requested period** If `ask` returns no email results, verify the time period phrasing (e.g., use "last 30 days" instead of a specific date range). The query is natural-language driven — overly precise date strings may not match. Retry with a broader phrase. **Incomplete or partial data** If `ask` returns fewer results than expected or omits certain metadata fields, compute analytics on the available data. Append a note to the dashboard: *"Some messages could not be fully retrieved and were excluded from analysis."* **Large volumes causing slow response** For periods longer than 90 days or inboxes with very high traffic (1 000+ messages), a single query may return incomplete results. In this case: - Reduce the analysis window (e.g., analyze one month at a time with separate `ask` calls). - Use `detail level: summary` to rely on aggregate counts only. **Sent folder unavailable** If the sent-mail query returns no results and the user expects sent data, confirm that the account's Sent Items folder is accessible. Set `include sent: false` to proceed with received-email analytics only. **Identity lookup failure** If `ask` cannot resolve the user profile, the dashboard still generates but displays the email address (from email results) instead of the display name. No analytics data is lost.