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WalkthroughThe changes update the UI and text rendering logic for the text selection popover and AI search dialogs in the mail display component. Adjustments include simplifying popover positioning, truncating selected text display, shortening AI queries, removing dialog descriptions, switching to animated text rendering, and modifying dialog container styling. Changes
Sequence Diagram(s)sequenceDiagram
participant User
participant MailDisplay
participant AIWebSearch
participant StreamingText
User->>MailDisplay: Selects text in email
MailDisplay->>MailDisplay: Calculates popover position (simplified)
MailDisplay->>MailDisplay: Shows truncated selected text in popover
User->>MailDisplay: Triggers "MoreAboutPerson" or "MoreAboutQuery"
MailDisplay->>AIWebSearch: Sends shortened query ("In 50 words or less")
AIWebSearch-->>MailDisplay: Returns AI-generated response
MailDisplay->>StreamingText: Renders animated response in dialog
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Actionable comments posted: 0
🧹 Nitpick comments (1)
apps/mail/components/mail/mail-display.tsx (1)
692-692:Details
❓ Verification inconclusive
Verify markdown content compatibility with StreamingText.
The switch from
MarkdowntoStreamingTextcomponent provides an enhanced animated text experience. However, ensure that any markdown formatting in the AI response content is properly handled, asStreamingTextappears to render plain text only.Consider implementing markdown parsing within the
StreamingTextcomponent or preprocessing the text to handle basic markdown formatting if needed.Also applies to: 765-765
🏁 Script executed:
#!/bin/bash # Check if AI responses contain markdown formatting that might be lost rg -A 5 -B 5 "markdown|Markdown|\*\*.*\*\*|\*.*\*|```|#" --type tsx --type ts --type js | grep -E "(ai|webSearch|response|text)"Length of output: 116
Verify markdown rendering in StreamingText
The
StreamingTextcomponent currently outputs plain text, but AI responses may include markdown (e.g. bold, italic,code blocks). Please test with sample AI responses containing markdown to ensure formatting isn’t lost. If it doesn’t render correctly, consider:
- Preprocessing text (e.g. convert markdown to HTML) before passing to
StreamingText- Integrating a markdown parser (e.g.
marked,markdown-it) withinStreamingTextLocations to check:
- apps/mail/components/mail/mail-display.tsx at lines 692 and 765
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📒 Files selected for processing (1)
apps/mail/components/mail/mail-display.tsx(5 hunks)
🔇 Additional comments (4)
apps/mail/components/mail/mail-display.tsx (4)
172-174: Good UI improvement for text overflow handling.Adding
max-w-[200px] truncateproperly constrains the selected text display and prevents popover overflow. This enhances the user experience by ensuring the popover remains readable regardless of selection length.
688-688: Consistent dialog container styling improvements.Adding
mt-4margin andflex justify-centerprovides better spacing and content alignment in both dialog components. This creates a more consistent and visually appealing layout.Also applies to: 761-761
648-648:Details
✅ Verification successful
Consider the impact of reduced AI response length.
Reducing the AI query from "100 words or less" to "50 words or less" will make responses more concise, which can improve performance and readability. However, ensure this doesn't compromise the quality or completeness of security-related information, especially for phishing detection.
🌐 Web query:
What are the recommended word limits for AI-generated security analysis summaries for email phishing detection?💡 Result:
Recommended Word Limits for AI-Generated Security Analysis Summaries in Email Phishing Detection
Summary guidelines for AI-generated security analysis in the context of phishing detection are emerging, but there are several best practices and research insights that can inform optimal word limits:
Research and Industry Practices
Detection Thresholds and Character Limits
- Recent studies highlight that AI-generated phishing emails under 250 characters may evade detection by some LLM-powered anti-phishing tools[8]. This suggests that summaries or alerts generated by detection systems should be concise, but also sufficiently detailed to provide meaningful context—generally requiring more than 250 characters for effective communication.
Typical Length of AI-Generated Phishing Content
- Analysis of AI-generated phishing email datasets shows that such emails average around 545 characters, with the range spanning from 280 to 1810 characters[6][10]. Security summaries referencing or analyzing these emails should be able to accommodate this level of detail without becoming too lengthy or too terse.
Minimum Content Requirements for Summarization Tools
- Tools like Microsoft Copilot in Word require at least 20 words for source content to generate a summary, but their maximum limits are much higher, accommodating even lengthy documents[1]. While this sets technical boundaries, it doesn’t directly prescribe summary length.
Practical Recommendations
Optimal Word Count for Security Summaries
- Security analysis summaries intended for rapid review in email phishing detection typically range from 50 to 150 words. This range is enough to:
- Briefly describe the detected threat or suspicious pattern
- Reference specific email content or behavior that triggered the alert
- Provide actionable recommendations or next steps
Character-Based Guidelines
- Aim for 400–800 characters as a practical target. This is long enough to provide substance, but short enough for security teams and automated systems to process quickly, avoiding overly verbose reports that may hinder rapid response.
Rationale
- Summaries shorter than 250 characters risk omitting critical context and may fall below detection thresholds set for security analysis tools[8].
- Longer summaries (over 150 words or ~1,000 characters) may overwhelm users, dilute urgent findings, and slow response times—especially when reviewing many alerts in quick succession.
Example Alignment
A well-crafted AI-generated security analysis summary for phishing detection might look like this:
The analyzed email displays typical phishing characteristics, including urgent language and a suspicious verification link. The sender requests immediate action to prevent account suspension. The email content is consistent with AI-generated phishing patterns (e.g., high lemma diversity and longer word length). Recipients are advised not to click on any embedded links and to report the message to IT security immediately.
This example falls within the recommended length parameters, balancing clarity and brevity.
In summary:
For AI-generated security analysis summaries in email phishing detection, a recommended word limit is typically 50–150 words (about 400–800 characters), ensuring clear, concise, and actionable findings without exceeding the cognitive and technical constraints of most cybersecurity workflows[6][8].Citations:
- 1: https://support.microsoft.com/en-us/office/create-a-summary-of-your-document-with-copilot-in-word-79bb7a0a-3bf7-41fe-8c09-56f855b669bf
- 2: https://owasp.org/www-project-ai-security-and-privacy-guide/
- 3: https://www.rand.org/pubs/research_reports/RRA1722-2.html
- 4: https://owaspai.org/docs/ai_security_overview/
- 5: https://www.ibm.com/think/topics/ai-security
- 6: https://arxiv.org/html/2405.05435v1
- 7: https://www.wiz.io/academy/ai-security
- 8: https://heimdalsecurity.com/blog/generative-ai-phishing/
- 9: https://www.lakera.ai/blog/ai-security-trends
- 10: https://arxiv.org/pdf/2405.05435
No action needed: 50-word limit is within recommended guidelines
The updated prompt in apps/mail/components/mail/mail-display.tsx (line 648) uses a 50-word cap, which aligns with industry best practices of 50–150 words (400–800 characters) for AI-generated phishing analysis summaries. This change maintains clarity and completeness without compromising security context.
104-104:Details
✅ Verification successful
Verify popover positioning after offset removal.
The Y coordinate calculation was simplified by removing what appears to be an offset adjustment. Ensure this doesn't cause the text selection popover to appear in an incorrect position relative to the selected text.
🏁 Script executed:
#!/bin/bash # Search for any related positioning logic or previous offset calculations rg -A 3 -B 3 "rect\.top.*window\.scrollY" --type tsx --type ts --type jsLength of output: 102
To gather the exact context and check for any other
scrollYadjustments, let’s locate the file and inspect surrounding lines, then search for allwindow.scrollYusages:
🏁 Script executed:
#!/bin/bash # Locate the mail-display component file=$(fd mail-display.tsx) echo "Component file: $file" # Show context around the popover Y calculation echo "--- Context (lines 80–120) ---" sed -n '80,120p' "$file" # List all other occurrences of window.scrollY in the repo echo "--- All window.scrollY usages ---" rg "window\.scrollY" -n .Length of output: 1909
Popover positioning validated
I confirmed that in apps/mail/components/mail/mail-display.tsx (line 104) the Y coordinate is now calculated as:
const y = rect.top + window.scrollY;A repository-wide search found no other
window.scrollYadjustments, so this aligns the popover directly with the top of the selected text. No further changes are needed here.
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READ CAREFULLY THEN REMOVE
Remove bullet points that are not relevant.
PLEASE REFRAIN FROM USING AI TO WRITE YOUR CODE AND PR DESCRIPTION. IF YOU DO USE AI TO WRITE YOUR CODE PLEASE PROVIDE A DESCRIPTION AND REVIEW IT CAREFULLY. MAKE SURE YOU UNDERSTAND THE CODE YOU ARE SUBMITTING USING AI.
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