FoundationAgents/OpenManus
Mar 2025 – Mar 2025
1 Month active
Languages Used
PythonTOML
Technical Skills
API UsageAgent DevelopmentBackend DevelopmentCode FormattingCode RefactoringConfiguration Management
zhiyuanRen
PROFILE
Zhiyuanren
During March 2025, this developer enhanced the FoundationAgents/OpenManus repository by implementing token-level visibility for large language model usage and introducing configurable Model Context Protocol settings. Using Python and TOML, they added detailed tracking and reporting of input and completion tokens, enabling cost analysis and improved usage transparency. Their work also addressed prompt context integrity by refining browser state handling and removing stale overrides, which improved reliability. Additionally, they stabilized memory usage through message throttling, preventing overuse and ensuring consistent performance. The developer demonstrated depth in backend development, configuration management, and LLM integration, delivering maintainable solutions to real deployment challenges.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
7Total
Bugs
2
Commits
7
Features
2
Lines of code
137
Activity Months1
Your Network
41 peopleWork History
March 2025
7 Commits • 2 Features
Mar 1, 2025March 2025 monthly summary for FoundationAgents/OpenManus: Implemented token-level visibility for LLM usage, introduced configurable MCP settings, stabilized memory usage through message throttling, and fixed prompt context integrity issues. These changes yield clearer cost visibility, improved reliability, and greater deployment flexibility, strengthening both business value and technical maintainability.
7 Commits • 2 Features
Mar 1, 2025March 2025 monthly summary for FoundationAgents/OpenManus: Implemented token-level visibility for LLM usage, introduced configurable MCP settings, stabilized memory usage through message throttling, and fixed prompt context integrity issues. These changes yield clearer cost visibility, improved reliability, and greater deployment flexibility, strengthening both business value and technical maintainability.
March 2025
Activity
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Quality Metrics
Correctness85.8%
Maintainability88.6%
Architecture82.8%
Performance85.8%
AI Usage25.8%
Skills & Technologies
Programming Languages
PythonTOML
Technical Skills
API UsageAgent DevelopmentBackend DevelopmentCode FormattingCode RefactoringConfiguration ManagementDebuggingInternationalizationLLM IntegrationLoggingPrompt EngineeringPythonResource Management
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