agentscope-ai/agentscope
Mar 2026 – Mar 2026
1 Month active
Languages Used
MarkdownPython
Technical Skills
Agent DevelopmentBug FixingCode RefactoringDocumentation Update
Haohao Luo
PROFILE
Haohao Luo
Worked on stabilizing the multi-turn Deep Research Agent within the agentscope-ai/agentscope repository, focusing on improving reliability and workflow clarity. Addressed a bug in reply handling by refining message extraction logic, ensuring accurate multi-turn conversation management. Enhanced temporary file organization by incorporating user queries into file names, which streamlines research traceability. Updated the project’s README in Markdown to provide clear guidelines for multi-turn interactions, supporting better onboarding and usage. Utilized Python for code refactoring and bug fixing, emphasizing maintainability and documentation quality. The work laid a foundation for scalable agent development, prioritizing robust conversation handling and improved developer experience.
Overall Statistics
Feature vs Bugs
0%Features
Repository Contributions
2Total
Bugs
1
Commits
2
Features
0
Lines of code
74
Activity Months1
Your Network
4716 peopleSame Organization
@users.noreply.github.com4701
Work History
March 2026
2 Commits
Mar 1, 2026Monthly summary for 2026-03: Stabilized multi-turn Deep Research Agent in agentscope, corrected reply handling and current-message extraction, improved temporary file naming to include user queries, and updated README with multi-turn conversation guidelines. These changes reduce confusion, improve research workflow reliability, and lay groundwork for scalable multi-turn interactions.
2 Commits
Mar 1, 2026Monthly summary for 2026-03: Stabilized multi-turn Deep Research Agent in agentscope, corrected reply handling and current-message extraction, improved temporary file naming to include user queries, and updated README with multi-turn conversation guidelines. These changes reduce confusion, improve research workflow reliability, and lay groundwork for scalable multi-turn interactions.
March 2026
Activity
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Quality Metrics
Correctness90.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
MarkdownPython
Technical Skills
Agent DevelopmentBug FixingCode RefactoringDocumentation Update
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