coze-dev/coze-loop
Feb 2026 – Mar 2026
2 Months active
Languages Used
Go
Technical Skills
API developmentThriftbackend developmentgRPCGodata validation
静音鸭子人
PROFILE
静音鸭子人
Worked on the coze-dev/coze-loop repository to deliver robust backend features supporting evaluation workflows and multi-modal data ingestion. Developed and enhanced API endpoints in Go, leveraging Thrift and gRPC to enable filtering, ordering, and importing of evaluation sets with precise total counts. Improved data validation and serialization by refining field naming and JSON tagging, ensuring reliable analytics and scalable ingestion. Addressed multipart DTO conversion issues and strengthened unit testing to maintain data integrity and prevent regressions. Aligned code generation and build workflows for stability, while OpenAPI/IDL adjustments and CI hygiene contributed to safer deployments and accelerated development cycles.
Overall Statistics
Feature vs Bugs
67%Features
Repository Contributions
4Total
Bugs
1
Commits
4
Features
2
Lines of code
51,143
Activity Months2
Your Network
22 peopleWork History
March 2026
3 Commits • 1 Features
Mar 1, 2026March 2026 — Key backend delivery for coze-loop focused on end-to-end evaluation workflows and robust multi-modal data ingestion. Delivered features include API endpoints for importing evaluation sets and managing evaluation set jobs, with improvements to data structures and validation to support multi-modal ingestion. Addressed major reliability gaps by fixing multipart DTO conversions and strengthening unit tests. Overall impact: accelerated evaluation pipelines, improved data integrity and scalability of ingestion workflows, and higher code quality through comprehensive testing and tooling. Technologies/skills demonstrated: Go backend, API design with OpenAPI/IDL, multi-modal data handling, data validation, unit testing, and CI hygiene.
3 Commits • 1 Features
Mar 1, 2026March 2026 — Key backend delivery for coze-loop focused on end-to-end evaluation workflows and robust multi-modal data ingestion. Delivered features include API endpoints for importing evaluation sets and managing evaluation set jobs, with improvements to data structures and validation to support multi-modal ingestion. Addressed major reliability gaps by fixing multipart DTO conversions and strengthening unit tests. Overall impact: accelerated evaluation pipelines, improved data integrity and scalability of ingestion workflows, and higher code quality through comprehensive testing and tooling. Technologies/skills demonstrated: Go backend, API design with OpenAPI/IDL, multi-modal data handling, data validation, unit testing, and CI hygiene.
March 2026
February 2026
1 Commits • 1 Features
Feb 1, 2026February 2026 monthly summary for the coze-loop development work, focusing on delivering a robust data filtering feature and improving code quality. The work centers on Evaluation Sets Filtering and Ordering with a precise total count, along with associated codegen and testing improvements to support reliable, scalable analytics.
February 2026
1 Commits • 1 Features
Feb 1, 2026February 2026 monthly summary for the coze-loop development work, focusing on delivering a robust data filtering feature and improving code quality. The work centers on Evaluation Sets Filtering and Ordering with a precise total count, along with associated codegen and testing improvements to support reliable, scalable analytics.
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage50.0%
Skills & Technologies
Programming Languages
Go
Technical Skills
API developmentGoThriftbackend developmentdata validationgRPCunit testing
Repositories Contributed To
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