Skyvern-AI/skyvern
Nov 2025 – Feb 2026
4 Months active
Languages Used
JavaScriptPythonTypeScriptYAMLMarkdown
Technical Skills
API DevelopmentAPI IntegrationAPI developmentBackend DevelopmentCloud ComputingDevOps
Marc Kelechava
PROFILE
Marc Kelechava
Marc contributed to the Skyvern-AI/skyvern repository by building and enhancing automation, workflow, and parsing systems that improved reliability, cost visibility, and developer experience. He implemented granular geo-targeting, robust PDF and image parsing with OCR, and session-based billing logic, using Python, React, and FastAPI. Marc developed hybrid browser automation tools and improved credential management, enabling secure, scalable workflow execution. His work included backend and frontend features, such as workflow templates and artifact handling with presigned URLs, while addressing race conditions and error handling. The engineering demonstrated depth in asynchronous programming, data validation, and secure API integration, resulting in resilient automation infrastructure.
Overall Statistics
Feature vs Bugs
69%Features
Repository Contributions
72Total
Bugs
16
Commits
72
Features
36
Lines of code
16,032
Activity Months4
Your Network
58 peopleSame Organization
@skyvern.com4
Work History
February 2026
10 Commits • 3 Features
Feb 1, 2026February 2026 performance summary for Skyvern-AI/skyvern focusing on stability, parsing robustness, and automation tooling that directly enhances business value and developer productivity. Key outcomes include robust handling of large PDFs, expanded image text extraction via OCR, a critical reliability fix for workflow end states, and a foundational MCP tooling platform enabling hybrid browser automation and scalable workflow execution. These improvements reduce failure modes, accelerate AI-assisted document workflows, and strengthen the end-to-end automation stack across parsing, validation, and execution.
10 Commits • 3 Features
Feb 1, 2026February 2026 performance summary for Skyvern-AI/skyvern focusing on stability, parsing robustness, and automation tooling that directly enhances business value and developer productivity. Key outcomes include robust handling of large PDFs, expanded image text extraction via OCR, a critical reliability fix for workflow end states, and a foundational MCP tooling platform enabling hybrid browser automation and scalable workflow execution. These improvements reduce failure modes, accelerate AI-assisted document workflows, and strengthen the end-to-end automation stack across parsing, validation, and execution.
February 2026
January 2026
15 Commits • 7 Features
Jan 1, 2026January 2026 monthly summary for Skyvern-AI/skyvern: This period delivered a focused set of features and reliability improvements that directly enhance cost visibility, geotargeting accuracy, workflow reliability, and developer experience. Key features delivered include GeoTargeting Enhancements (PH proxy support, improved subdivision input validation, stronger country/state/city logic, with robust lazy-loading and a race-condition fix), Billing Improvements (per-action credit tracking, action-count retrieval per step, new billing ID generation, and session-based cost metering with indexing to boost metering performance), Workflow and Webhook Improvements (step-count tracking in webhooks and run payloads, finally blocks in workflows, and a comprehensive workflow run payload), Print Page Block Enhancements (PDF generation with advanced settings and debugging), and HTTP File Download plus Jinja JSON Type Injection Filter (HTTP downloads with user-specified filenames and improved templating for HTTP blocks). Additional improvements include storing screenshot artifacts with presigned URLs for easy retrieval. Major bugs fixed include File Encoding Robustness (improved encoding detection in FileParserBlock to prevent decoding errors), a race condition fix in the lazy-loaded geo search module, and privacy hardening to Hide Billing Endpoints in Fern docs. Overall impact: The month delivered substantially improved cost metering accuracy, more reliable geotargeting and workflow execution, enhanced debugging and visibility for developers, and safer documentation practices, contributing directly to business value through better cost control, reliability, and developer productivity. Technologies/skills demonstrated: Lazy-loading and race-condition debugging, per-action billing logic and session-based metering, enhanced webhook/workflow payloads, PDF generation, HTTP file transfer, Jinja templating enhancements, and secure documentation practices (presigned URLs, hidden endpoints).
January 2026
15 Commits • 7 Features
Jan 1, 2026January 2026 monthly summary for Skyvern-AI/skyvern: This period delivered a focused set of features and reliability improvements that directly enhance cost visibility, geotargeting accuracy, workflow reliability, and developer experience. Key features delivered include GeoTargeting Enhancements (PH proxy support, improved subdivision input validation, stronger country/state/city logic, with robust lazy-loading and a race-condition fix), Billing Improvements (per-action credit tracking, action-count retrieval per step, new billing ID generation, and session-based cost metering with indexing to boost metering performance), Workflow and Webhook Improvements (step-count tracking in webhooks and run payloads, finally blocks in workflows, and a comprehensive workflow run payload), Print Page Block Enhancements (PDF generation with advanced settings and debugging), and HTTP File Download plus Jinja JSON Type Injection Filter (HTTP downloads with user-specified filenames and improved templating for HTTP blocks). Additional improvements include storing screenshot artifacts with presigned URLs for easy retrieval. Major bugs fixed include File Encoding Robustness (improved encoding detection in FileParserBlock to prevent decoding errors), a race condition fix in the lazy-loaded geo search module, and privacy hardening to Hide Billing Endpoints in Fern docs. Overall impact: The month delivered substantially improved cost metering accuracy, more reliable geotargeting and workflow execution, enhanced debugging and visibility for developers, and safer documentation practices, contributing directly to business value through better cost control, reliability, and developer productivity. Technologies/skills demonstrated: Lazy-loading and race-condition debugging, per-action billing logic and session-based metering, enhanced webhook/workflow payloads, PDF generation, HTTP file transfer, Jinja templating enhancements, and secure documentation practices (presigned URLs, hidden endpoints).
December 2025
33 Commits • 19 Features
Dec 1, 2025December 2025 performance summary for Skyvern: Delivered a range of features, reliability fixes, and security improvements across frontend, backend, and documentation, with a strong focus on business value and developer productivity.
33 Commits • 19 Features
Dec 1, 2025December 2025 performance summary for Skyvern: Delivered a range of features, reliability fixes, and security improvements across frontend, backend, and documentation, with a strong focus on business value and developer productivity.
December 2025
November 2025
14 Commits • 7 Features
Nov 1, 2025November 2025 monthly summary for Skyvern (Skyvern-AI/skyvern). This month delivered significant features and reliability improvements across CI personalization, browser profiles, UX for 2FA, Vertex AI authentication, geo-targeting, and Discover UI, driving security, scalability, and monetization of cached steps. Key outcomes include stable browser profile creation with DB/S3 storage, enhanced GitHub Actions personalization, Google Cloud Workload Identity support for Vertex models, expanded geo-targeting, and a refreshed Discover page.
November 2025
14 Commits • 7 Features
Nov 1, 2025November 2025 monthly summary for Skyvern (Skyvern-AI/skyvern). This month delivered significant features and reliability improvements across CI personalization, browser profiles, UX for 2FA, Vertex AI authentication, geo-targeting, and Discover UI, driving security, scalability, and monetization of cached steps. Key outcomes include stable browser profile creation with DB/S3 storage, enhanced GitHub Actions personalization, Google Cloud Workload Identity support for Vertex models, expanded geo-targeting, and a refreshed Discover page.
Activity
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Quality Metrics
Correctness91.4%
Maintainability83.8%
Architecture85.8%
Performance83.6%
AI Usage42.6%
Skills & Technologies
Programming Languages
JavaScriptMarkdownPythonTypeScriptYAML
Technical Skills
AI IntegrationAI integrationAI/MLAPI DevelopmentAPI DocumentationAPI IntegrationAPI developmentAPI integrationAWS S3 integrationAutomationBackend DevelopmentCloud ComputingDevOpsDocumentationError handling
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