kilian-group/phantom-wiki
Jan 2025 – Jan 2025
1 Month active
Languages Used
Python
Technical Skills
Code CleanupDatabase IntegrationDatabase InteractionDebuggingNatural Language ProcessingProlog
Mihir Rajnish Mishra
PROFILE
Mihir Rajnish Mishra
During January 2025, Michael M. contributed to the kilian-group/phantom-wiki repository by developing Prolog-based data retrieval through agent prompts, enabling dynamic generation and validation of Prolog queries for database interaction. He integrated these queries with the existing Database class, implemented query splitting for complex prompts, and established automated testing against facts.pl to ensure correctness. Using Python and Prolog, Michael also improved code quality by removing unnecessary debug output from the NshotAgent, resulting in cleaner logs and a better developer experience. His work demonstrated depth in prompt engineering, database integration, and debugging, addressing both functionality and maintainability within the project.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
4Total
Bugs
1
Commits
4
Features
1
Lines of code
192
Activity Months1
Your Network
12 people
Work History
January 2025
4 Commits • 1 Features
Jan 1, 2025January 2025: Delivered Prolog-based data retrieval via agent prompts and integrated Prolog query handling with the Database class. Implemented query splitting for complex prompts, wired validation against facts.pl, and established testing coverage to ensure correctness of generated queries. Also cleaned development output by removing debug prints from NshotAgent, resulting in cleaner logs and improved user-facing messaging. These changes enhance data retrieval capabilities, reliability of prompt-driven queries, and developer experience.
4 Commits • 1 Features
Jan 1, 2025January 2025: Delivered Prolog-based data retrieval via agent prompts and integrated Prolog query handling with the Database class. Implemented query splitting for complex prompts, wired validation against facts.pl, and established testing coverage to ensure correctness of generated queries. Also cleaned development output by removing debug prints from NshotAgent, resulting in cleaner logs and improved user-facing messaging. These changes enhance data retrieval capabilities, reliability of prompt-driven queries, and developer experience.
January 2025
Activity
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Quality Metrics
Correctness92.6%
Maintainability90.0%
Architecture90.0%
Performance82.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Code CleanupDatabase IntegrationDatabase InteractionDebuggingNatural Language ProcessingPrologPrompt EngineeringSoftware Development
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