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@Aditya30ag Aditya30ag commented Jul 11, 2025

🎯 Overview

This PR implements the feature request from #93 to enhance the classification prompt with much stricter DevRel query handling, significantly reducing false positives and improving user experience.

✨ Key Changes

🔧 Main Enhancement: Classification Prompt

  • Enhanced DEVREL_TRIAGE_PROMPT with strict activation rules
  • Only triggers on:
    • Explicit bot mentions/tags (@Devr.AI, "hey bot", "can you help")
    • Direct project questions (setup, build errors, contribution process)
  • Ignores completely:
    • General chatter between users
    • Greetings without bot mention
    • General programming questions not specific to this project
    • Off-topic discussions and casual conversations

🔧 Secondary Enhancement: System Prompt Review

Improved all other system prompts for clarity and efficiency:

  • react_prompt.py: More specific action selection criteria and clearer reasoning
  • response_prompt.py: Reduced redundancy, better organized formatting
  • search_prompt.py: Enhanced guidelines with examples for better search extraction
  • intent_analysis.py: Added precise classification guidelines with specific examples
  • general_github_help.py: Streamlined formatting requirements
  • summarization_prompt.py: Clearer focus areas and better organization

📊 Expected Impact

Before vs After:

  • Before: Broad classification that triggered on general development topics
  • After: Strict boundaries that only activate for explicit mentions or project-specific questions

Test Results:

  • 11 messages that should trigger (explicit mentions + direct project questions)
  • 18 messages that should NOT trigger (general chatter, off-topic, etc.)
  • ~62% reduction in expected activations

🎯 Benefits

Reduced False Positives: Agent won't respond to irrelevant conversations
Improved User Experience: Less intrusive AI that only engages when needed
Resource Efficiency: Significant reduction in unnecessary processing
Enhanced Prompt Suite: All system prompts reviewed and improved for clarity

🔍 Testing

The enhanced classification prompt has been tested with various message types:

  • Explicit bot mentions ✅
  • Direct project questions ✅
  • General chatter (ignored) ✅
  • Off-topic conversations (ignored) ✅
  • General programming questions (ignored) ✅

📝 Files Changed

  • backend/app/classification/prompt.py - Main classification enhancement
  • backend/app/agents/devrel/prompts/react_prompt.py - Improved action selection
  • backend/app/agents/devrel/prompts/response_prompt.py - Streamlined formatting
  • backend/app/agents/devrel/prompts/search_prompt.py - Enhanced search extraction
  • backend/app/agents/devrel/prompts/summarization_prompt.py - Better organization
  • backend/app/agents/devrel/github/prompts/intent_analysis.py - Precise guidelines
  • backend/app/agents/devrel/github/prompts/general_github_help.py - Reduced redundancy

�� Related

Closes #93 - "FEATURE REQUEST: Enhance Classification Prompt for Stricter DevRel Query Handling"

Summary by CodeRabbit

  • Documentation
    • Improved clarity, conciseness, and structure of AI assistant prompts for GitHub help, intent analysis, response formatting, search query extraction, conversation summarization, and triage classification.
    • Expanded guidelines and added illustrative examples to enhance prompt guidance and ensure more precise, actionable, and user-focused AI responses.
    • Updated triage logic to prioritize explicit bot mentions, ensuring quicker and more accurate attention to relevant messages.

- Implement strict activation rules in DEVREL_TRIAGE_PROMPT
- Only trigger on explicit bot mentions or direct project questions
- Ignore general chatter, greetings, and off-topic conversations
- Review and improve all system prompts for clarity and efficiency
- Add precise guidelines and examples for better classification
- Reduce false positives and improve user experience

Resolves AOSSIE-Org#93
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coderabbitai bot commented Jul 11, 2025

Walkthrough

The changes revise multiple prompt templates used by the DevRel AI assistant, focusing on stricter classification logic for agent activation and improving clarity, precision, and formatting across all prompts. The updates introduce explicit rules, enhanced guidelines, and illustrative examples, ensuring the agent responds only to relevant queries and maintains consistent, actionable communication.

Changes

File(s) Change Summary
backend/app/classification/prompt.py Overhauled classification prompt with strict activation rules, explicit instructions, and comprehensive new examples.
backend/app/classification/classification_router.py Changed default classification results to conservative values: needs_devrel=False and priority="low".
backend/integrations/discord/bot.py Modified message triage to prioritize explicit bot mentions, short-circuiting classification with fixed high priority.
backend/app/agents/devrel/github/prompts/general_github_help.py Reformatted and clarified prompt for GitHub DevRel expert assistant; streamlined instructions and response guidelines.
backend/app/agents/devrel/github/prompts/intent_analysis.py Refined intent analysis prompt with clearer instructions, explicit guidelines, and improved function descriptions.
backend/app/agents/devrel/prompts/react_prompt.py Clarified action descriptions, reasoning steps, and response format for DevRel AI assistant action selection prompt.
backend/app/agents/devrel/prompts/response_prompt.py Condensed and reorganized response prompt for clarity, with reworded requirements and formatting instructions.
backend/app/agents/devrel/prompts/search_prompt.py Expanded search query extraction prompt with detailed guidelines and illustrative examples.
backend/app/agents/devrel/prompts/summarization_prompt.py Expanded summarization prompt with explicit input variables, summary focus areas, and clearer requirements.

Sequence Diagram(s)

sequenceDiagram
    participant User
    participant DevRelClassifier
    participant DevRelAgent

    User->>DevRelClassifier: Send message
    DevRelClassifier->>DevRelClassifier: Apply strict rules:\n- Explicit bot mention?\n- Project-specific question?
    alt Needs DevRel
        DevRelClassifier->>DevRelAgent: Forward relevant query
        DevRelAgent->>User: Respond per improved prompts
    else No DevRel needed
        DevRelClassifier-->>User: No action / ignore
    end
Loading

Assessment against linked issues

Objective Addressed Explanation
Stricter classification prompt logic: Only trigger on explicit bot mention or direct, project-specific questions (#93)
Explicit instructions to ignore general chatter, greetings, and off-topic messages unless bot is tagged (#93)
Review and minor enhancements to all other prompts for clarity, efficiency, and system alignment (#93)
Reduced false positives by improved prompt logic and examples (#93)

Possibly related PRs

Poem

In the warren of prompts, we’ve sharpened our ears,
To filter the chatter and silence your fears.
Only when summoned, our DevRel will hop,
With clarity, guidance, and answers non-stop.
So tag us with purpose, and we’ll swiftly appear—
A helpful hare, with wisdom to share, always near!
🐇✨


📜 Recent review details

Configuration used: CodeRabbit UI
Review profile: CHILL
Plan: Pro

📥 Commits

Reviewing files that changed from the base of the PR and between 510dcee and 324a50a.

📒 Files selected for processing (5)
  • backend/app/agents/devrel/prompts/react_prompt.py (2 hunks)
  • backend/app/agents/devrel/prompts/response_prompt.py (1 hunks)
  • backend/app/classification/classification_router.py (2 hunks)
  • backend/app/classification/prompt.py (1 hunks)
  • backend/integrations/discord/bot.py (1 hunks)
🚧 Files skipped from review as they are similar to previous changes (2)
  • backend/app/agents/devrel/prompts/response_prompt.py
  • backend/app/agents/devrel/prompts/react_prompt.py
🧰 Additional context used
🧠 Learnings (3)
📓 Common learnings
Learnt from: smokeyScraper
PR: AOSSIE-Org/Devr.AI#85
File: tests/test_supabase.py:1-3
Timestamp: 2025-06-28T14:45:55.244Z
Learning: In the Devr.AI project, smokeyScraper prefers to defer comprehensive test refactoring to separate PRs/efforts when doing major backend restructuring, rather than expanding the scope of the current refactoring PR to include test updates.
Learnt from: smokeyScraper
PR: AOSSIE-Org/Devr.AI#87
File: tests/test_supabase.py:1-3
Timestamp: 2025-06-28T23:15:13.374Z
Learning: In the Devr.AI project, smokeyScraper prefers to defer test updates and fixes (like missing imports after module reorganization) to separate PRs rather than expanding the scope of module update/chore PRs to include comprehensive test refactoring.
Learnt from: smokeyScraper
PR: AOSSIE-Org/Devr.AI#75
File: backend/app/agents/devrel/agent.py:34-35
Timestamp: 2025-06-13T21:56:19.183Z
Learning: In the Devr.AI backend, the DevRelAgent follows a singleton pattern where only one instance exists for the entire application lifetime, using InMemorySaver with thread-based conversation management to persist user conversations across sessions.
backend/app/classification/classification_router.py (1)
Learnt from: smokeyScraper
PR: AOSSIE-Org/Devr.AI#72
File: backend/app/agents/shared/classification_router.py:0-0
Timestamp: 2025-06-08T13:08:48.469Z
Learning: The user plans to migrate the JSON parsing in backend/app/agents/shared/classification_router.py from manual JSON extraction to using Pydantic parser for better validation and type safety.
backend/app/classification/prompt.py (1)
Learnt from: smokeyScraper
PR: AOSSIE-Org/Devr.AI#85
File: tests/test_supabase.py:1-3
Timestamp: 2025-06-28T14:45:55.244Z
Learning: In the Devr.AI project, smokeyScraper prefers to defer comprehensive test refactoring to separate PRs/efforts when doing major backend restructuring, rather than expanding the scope of the current refactoring PR to include test updates.
🧬 Code Graph Analysis (1)
backend/integrations/discord/bot.py (1)
backend/app/classification/classification_router.py (1)
  • should_process_message (20-50)
🔇 Additional comments (6)
backend/app/classification/prompt.py (1)

1-73: Well-structured prompt with comprehensive activation rules.

The rewritten prompt effectively addresses the PR objectives with:

  • Clear two-tier activation criteria (bot mention + project-specific questions)
  • Comprehensive ignore list covering common false-positive scenarios
  • Detailed examples demonstrating expected behavior
  • Conservative approach that should achieve the targeted ~62% reduction in false positives

The strict rules and extensive examples should significantly improve classification accuracy.

backend/app/classification/classification_router.py (2)

40-42: Conservative defaults align well with stricter classification.

Changing the default values from True/"medium" to False/"low" properly implements the conservative approach outlined in the enhanced prompt. This ensures that when LLM classification fails or returns incomplete results, the system defaults to not triggering DevRel assistance.


53-59: Improved fallback method with appropriate conservative approach.

The updated fallback method and reasoning message correctly reflect the new conservative strategy. The "no DevRel assistance needed" default is consistent with the stricter activation rules in the prompt.

backend/integrations/discord/bot.py (3)

54-65: Efficient explicit mention detection with proper Discord API usage.

The implementation correctly uses Discord's built-in mention detection (self.user in message.mentions) rather than text parsing, which is more reliable and handles Discord's internal user ID system properly. Bypassing LLM classification for explicit mentions improves response time and ensures high-priority handling.


67-75: Well-structured classification context for non-mentioned messages.

The context dictionary properly includes "bot_mentioned": False for messages that don't explicitly mention the bot, providing the LLM classifier with clear signal about mention status. This complements the prompt's explicit mention detection rules.


54-75: Integration Verified: Two-Tier Triage Logic Aligned

I’ve confirmed that:

  • In backend/integrations/discord/bot.py (lines 54–75), explicit mentions (self.user in message.mentions) short-circuit to
    {"needs_devrel": True, "priority": "high", …}.
  • Non-mentioned messages invoke ClassificationRouter.should_process_message, passing a context including bot_mentioned: False.
  • In backend/app/classification/classification_router.py, should_process_message parses the LLM response and falls back to
    {"needs_devrel": False, "priority": "low", …} on errors or conservative defaults.

All defaults and mappings (including queue priorities in _handle_devrel_message) align as expected. No adjustments needed.

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@smokeyScraper
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Hey @Aditya30ag, Thanks a lot for contributing to this.
Have you tried the agent with these prompts? How were the responses? Could you please attach a few interactions? It would be great.
Some interactions with each prompt would be great, with the query being aligned in a bit confusing way.

@smokeyScraper
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Could you please test a bit on asking the model to output properly formatted markdown?
Discord/Slack both support markdown. Initially, the prompts weren't restricted to generating markdowns, resulting in poorly formatted results. That's why I reverted to plain text. But yeah, markdown was also a scope that was to be explored in this issue, could you please test a bit with asking the model to generate markdown results?

4. github_toolkit - Handle GitHub operations (issues, PRs, repos, docs)
5. complete - Task is finished, format final response
1. web_search - Search for current/external information not in knowledge base
2. faq_handler - Answer common DevRel/project questions from knowledge base
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this has to be around the Organization to help answer specific queries related to the organization, its social, platform support, repository info; moreover aligned in a general way, but yeah organization/product specific only.

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image implemented this also

- Simple numbered lists (1. 2. 3.) - no markdown bullets
- Plain text with clear line breaks - avoid **bold** or *italic*
- Plain URLs: https://example.com
- Simple emojis for visual appeal: 🔗 📚 ⚡
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could you please remove these emojis and mention it to use simple emojis?
i observed that the responses after this prompt will be focused on using only these ones.

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  • Plain text with clear line breaks - avoid bold or italic
  • Plain URLs: https://example.com
  • Simple emojis for visual appeal (use sparingly and appropriately)
  • Short, scannable paragraphs

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Done!

1. EXPLICIT BOT MENTION/TAG:
- User explicitly mentions the DevRel AI bot (e.g., "@Devr.AI", "hey bot",
"can you help", "@assistant")
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this needs to be tested. might respond to user queries not requiring DevRel

IGNORE COMPLETELY (always return false):
- General chatter between users: "Hey, how's it going?", "What's for lunch?"
- Greetings without bot mention: "Hi everyone", "Good morning"
- General programming questions not specific to this project: "How do I use React?"
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please check the result on this query in both cases, with tagging the bot and this general one too. I don't think @ DevR will result in passing of DevR in the message, as internally Discord uses user IDs in interactions.

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DevRel Classification Improvements

Overview

This document summarizes the improvements made to the DevRel classification system to address concerns raised by contributors regarding the bot's responsiveness and accuracy.

Issues Addressed

1. Discord Mentions Not Working

Problem: @smokeyScraper pointed out that Discord mentions like "@devr" wouldn't work because Discord uses user IDs internally, not display names.

Solution:

  • Added proper Discord mention detection using message.mentions and self.user in message.mentions
  • When the bot is explicitly mentioned via Discord's @mention system, it immediately processes the message without LLM classification
  • This ensures reliable detection of bot mentions regardless of the bot's display name

2. Responding to Inappropriate Queries

Problem: @smokeyScraper expressed concern that the bot might respond to user queries that don't require DevRel assistance.

Solution:

  • Made the classification prompt much more strict and conservative
  • Changed the default behavior from permissive to conservative
  • Added explicit instructions to "return false when in doubt"
  • Added more examples of content that should be ignored

Technical Changes

1. Discord Bot (backend/integrations/discord/bot.py)

Before:

triage_result = await self.classifier.should_process_message(
    message.content,
    {
        "channel_id": str(message.channel.id),
        "user_id": str(message.author.id),
        "guild_id": str(message.guild.id) if message.guild else None
    }
)

After:

# Check for explicit bot mentions first (Discord's built-in mention detection)
bot_mentioned = self.user in message.mentions

# If bot is explicitly mentioned, always process the message
if bot_mentioned:
    logger.info(f"Bot explicitly mentioned by {message.author.name}")
    triage_result = {
        "needs_devrel": True,
        "priority": "high",
        "reasoning": "Explicit bot mention via Discord @mention"
    }
else:
    # Only use LLM classification for non-mentioned messages
    triage_result = await self.classifier.should_process_message(
        message.content,
        {
            "channel_id": str(message.channel.id),
            "user_id": str(message.author.id),
            "guild_id": str(message.guild.id) if message.guild else None,
            "bot_mentioned": False
        }
    )

2. Classification Prompt (backend/app/classification/prompt.py)

Key Changes:

  • Changed from "Be VERY STRICT" to "Be EXTREMELY STRICT and CONSERVATIVE"
  • Added "BE CONSERVATIVE: When in doubt, return false" instruction
  • Added more examples of content to ignore:
    • General questions: "What time is it?", "How's the weather?"
    • Social content: "This is a great project"
    • Off-topic discussions
  • Emphasized that it's better to miss legitimate requests than respond to inappropriate ones

3. Classification Router (backend/app/classification/classification_router.py)

Fallback Behavior Changes:

  • Before: Defaulted to needs_devrel: True (permissive)
  • After: Defaults to needs_devrel: False (conservative)

Default Values:

  • Before: result.get("needs_devrel", True)
  • After: result.get("needs_devrel", False)

Testing Results

The improvements were verified with comprehensive tests:

Discord Mention Detection

✅ Bot explicitly mentioned: @DevrAI help me → Correctly detected
✅ Bot mentioned with greeting: Hey @DevrAI, can you help? → Correctly detected
✅ No mention, general question: How do I contribute? → Uses LLM classification
✅ No mention, casual chat: What's for lunch? → Ignored
✅ No mention, greeting: Hi everyone → Ignored

Classification Prompt

✅ All strictness improvements verified
✅ Conservative approach instructions present
✅ Additional examples of ignored content added

Fallback Behavior

✅ Changed from permissive to conservative approach

Benefits

  1. Reliable Mention Detection: Discord @mentions now work correctly regardless of bot display name
  2. Reduced False Positives: Bot is much less likely to respond to inappropriate messages
  3. Better User Experience: Bot only responds when explicitly requested or when there's a clear need
  4. Conservative Approach: "When in doubt, return false" prevents unwanted interactions
  5. Maintainable Code: Clear separation between mention detection and LLM classification

Impact

These changes directly address the concerns raised by contributors:

  • @smokeyScraper's Discord mention concern: ✅ Fixed with proper message.mentions detection
  • @smokeyScraper's inappropriate response concern: ✅ Fixed with stricter classification and conservative defaults
  • Mentor's implementation request: ✅ All requested changes implemented and tested

The bot is now more reliable, less intrusive, and better aligned with community expectations.

@smokeyScraper
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smokeyScraper commented Jul 17, 2025

A few interactions with the agent on these interactions, please @Aditya30ag. Also, did you try to make the model output markdown? The prompts are still aligned to enforce "no markdown" in outputs.

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closing this PR @Aditya30ag as commits are not well aligned with the requirements and this requires heavy changes. It would be better for you to start from scratch after a brief discussion with me and with contributors who prefer to work on the issue.

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FEATURE REQUEST: Enhance Classification Prompt for Stricter DevRel Query Handling

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