wolfpld/tracy
May 2026 – Jul 2026
3 Months active
Languages Used
C++Python
Technical Skills
API developmentasynchronous programmingdata compressionfile handlingC++Profiling
Alan Tse
PROFILE
Alan Tse
Contributed to the wolfpld/tracy repository by developing and enhancing profiling and backend features over a three-month period. Delivered a new asynchronous snapshot tool for capturing live or loaded trace data, integrating with existing concurrency mechanisms and updating documentation for clarity. Extended Python bindings to expose code section instrumentation, enabling precise retrieval of timed segments for evaluation tools. Addressed documentation inconsistencies to improve user guidance. Implemented robust memory management and lifecycle controls for the Tracy MCP server, introducing configurable caps and idle-timeout cleanup to ensure stable long-running operation. Work utilized C++, Python, asynchronous programming, and memory management to address production-scale needs.
Overall Statistics
Feature vs Bugs
75%Features
Repository Contributions
4Total
Bugs
1
Commits
4
Features
3
Lines of code
343
Activity Months3
Work History
July 2026
1 Commits • 1 Features
Jul 1, 2026July 2026: Implemented memory management and lifecycle controls for the Tracy MCP server to prevent unbounded memory growth, improve stability of long-lived singleton processes, and enhance observability. Core work includes environment-configurable memory caps, idle-timeout cleanup, explicit eviction shutdown, and updated documentation for lifecycle management. This enables safer long-running operation, clearer operator guidance, and improved post-session analysis.
1 Commits • 1 Features
Jul 1, 2026July 2026: Implemented memory management and lifecycle controls for the Tracy MCP server to prevent unbounded memory growth, improve stability of long-lived singleton processes, and enhance observability. Core work includes environment-configurable memory caps, idle-timeout cleanup, explicit eviction shutdown, and updated documentation for lifecycle management. This enables safer long-running operation, clearer operator guidance, and improved post-session analysis.
July 2026
June 2026
2 Commits • 1 Features
Jun 1, 2026June 2026 monthly summary for wolfpld/tracy. Delivered end-to-end instrumentation exposure for MCP-based evaluation by binding Worker::GetSections() as get_sections(), enabling retrieval of timed code sections with start/end timestamps in nanoseconds for MCP tooling. Updated documentation to reflect the new accessor and MCP usage. Fixed a documentation issue by removing a dangling tracy://catalog reference in the MCP evaluation guide, preventing agents from reading unregistered resources and clarifying common query patterns.
June 2026
2 Commits • 1 Features
Jun 1, 2026June 2026 monthly summary for wolfpld/tracy. Delivered end-to-end instrumentation exposure for MCP-based evaluation by binding Worker::GetSections() as get_sections(), enabling retrieval of timed code sections with start/end timestamps in nanoseconds for MCP tooling. Updated documentation to reflect the new accessor and MCP usage. Fixed a documentation issue by removing a dangling tracy://catalog reference in the MCP evaluation guide, preventing agents from reading unregistered resources and clarifying common query patterns.
May 2026
1 Commits • 1 Features
May 1, 2026May 2026 Monthly Summary for wolfpld/tracy: Delivered the Profiling: Save Trace Snapshot Tool (save_trace) to extend Tracy's profiling capabilities by enabling snapshot captures of live or loaded traces via a new MCP tool. The feature is designed for production-scale traces and integrates with the existing concurrency and task machinery to ensure safe, asynchronous saves. Documentation updated to reflect the new tool.
1 Commits • 1 Features
May 1, 2026May 2026 Monthly Summary for wolfpld/tracy: Delivered the Profiling: Save Trace Snapshot Tool (save_trace) to extend Tracy's profiling capabilities by enabling snapshot captures of live or loaded traces via a new MCP tool. The feature is designed for production-scale traces and integrates with the existing concurrency and task machinery to ensure safe, asynchronous saves. Documentation updated to reflect the new tool.
May 2026
Activity
Loading activity data...
Quality Metrics
Correctness100.0%
Maintainability95.0%
Architecture100.0%
Performance90.0%
AI Usage75.0%
Skills & Technologies
Programming Languages
C++Python
Technical Skills
API developmentC++ProfilingPythonasynchronous programmingasynciobackend developmentdata compressiondocumentationfile handlingmcpmemory managementpybind11python
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline