self_reflection

[mrT23]

PR Type

Enhancement, Documentation

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Description

• Added comprehensive documentation for the self-reflection and suggestion ranking feature in PR-Agent
• Introduced the hierarchical structure for efficient suggestion review:
  • Category-based grouping
  • One-line summaries with expandable details
  • Code snippets for each suggestion
• Explained the self-reflection process:
  • Follow-up call to score and rationalize suggestions
  • Re-ranking based on scores
  • Filtering out incorrect or low-scoring suggestions
• Included visual examples of the feature in action
• Added configuration options for self-reflection and suggestion scoring

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Changes walkthrough 📝

	Relevant files
Documentation	self_reflection.md Detailed documentation on self-reflection and suggestion ranking docs/docs/core-abilities/self_reflection.md Added comprehensive documentation on self-reflection and suggestion ranking Explained the hierarchical structure for presenting suggestions Described the self-reflection process and its benefits Included example results and configuration options +43/-2

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💡 PR-Agent usage:
Comment /help on the PR to get a list of all available PR-Agent tools and their descriptions

[codiumai-pr-agent-pro]

PR Reviewer Guide 🔍

⏱️ Estimated effort to review: 2 🔵🔵⚪⚪⚪

🏅 Score: 95

🧪 No relevant tests

🔒 No security concerns identified

🔀 No multiple PR themes

⚡ No key issues to review

[codiumai-pr-agent-pro]

PR Code Suggestions ✨

Category	Suggestion	Score
Enhancement	✅ Provide information on how users can interpret and use suggestion scores Suggestion Impact: The commit implemented part of the suggestion by adding the scoring scale (0-10) to the documentation. code diff: +2. Instructing the model to score each suggestion on a scale of 0-10 and provide a rationale for the assigned score. Consider adding a brief explanation of how users can interpret and utilize the scores assigned to suggestions during the self-reflection process. This information would help users make more informed decisions when reviewing suggestions. docs/docs/core-abilities/self_reflection.md [24-26] -2. Instructing the model to score each suggestion and provide a rationale for the assigned score. +2. Instructing the model to score each suggestion on a scale of 0-10 and provide a rationale for the assigned score. 3. Utilizing these scores to re-rank the suggestions and filter out incorrect ones (with a score of 0). 4. Optionally, filtering out all suggestions below a user-defined score threshold. +5. Presenting the scores to users, allowing them to quickly assess the perceived importance of each suggestion. Apply this suggestion Suggestion importance[1-10]: 9 Why: This suggestion significantly improves the documentation by explaining the scoring system and how users can leverage it, which is crucial for effective use of the feature.	9
	Add information about the impact of self-reflection on user experience Consider adding a brief explanation of how the self-reflection process impacts the user experience and the overall quality of suggestions. This could help readers better understand the practical benefits of this feature. docs/docs/core-abilities/self_reflection.md [30] -To conclude, the self-reflection process enables PR-Agent to prioritize suggestions based on their importance, eliminate inaccurate or irrelevant proposals, and optionally exclude suggestions that fall below a specified threshold of significance. +To conclude, the self-reflection process enables PR-Agent to prioritize suggestions based on their importance, eliminate inaccurate or irrelevant proposals, and optionally exclude suggestions that fall below a specified threshold of significance. This results in a more refined and valuable set of suggestions for the user, saving time and improving the overall code review experience. Apply this suggestion Suggestion importance[1-10]: 8 Why: This suggestion adds valuable context about the practical benefits of the self-reflection process, enhancing user understanding and highlighting its importance.	8
	Add information about the performance impact of the self-reflection process Consider adding a brief explanation of the time complexity or performance impact of the self-reflection process. This information would be valuable for users concerned about the efficiency of the PR-Agent. docs/docs/core-abilities/self_reflection.md [14-21] ### Self-reflection and re-ranking The AI model is initially tasked with generating suggestions, and outputting them in order of importance. However, in practice we observe that models often struggle to simultaneously generate high-quality code suggestions and rank them well in a single pass. Furthermore, the initial set of generated suggestions occasionally contains readily identifiable errors. To address these issues, we implemented a "self-reflection" process that refines suggestion ranking and eliminates irrelevant or incorrect proposals. This process consists of the following steps: +Note: The self-reflection process adds a small overhead to the suggestion generation time, but significantly improves the quality and relevance of the final output. The additional time is typically negligible compared to the time saved during manual review of the suggestions. + Apply this suggestion Suggestion importance[1-10]: 7 Why: This suggestion adds useful information about the efficiency trade-offs of the self-reflection process, which is valuable for users concerned about performance.	7

[mrT23]

/analyze

[codiumai-pr-agent-pro]

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