archestra-ai/archestra
Nov 2025 – Jan 2026
3 Months active
Languages Used
DockerfileJavaScriptSQLShellTypeScriptYAMLBashJSON
Technical Skills
API developmentAPI integrationContainerizationContinuous IntegrationDevOpsDocker
Anna Shishlyakova
PROFILE
Anna Shishlyakova
Worked on the archestra-ai/archestra repository to deliver robust platform features focused on security, cost optimization, and governance. Over three months, built and refined authentication flows, automated secret management with Helm and Dockerfile, and implemented token-based optimization rules for LLM cost control. Enhanced policy management by introducing per-tool policy frameworks and contextual evaluation, while improving UI/UX for chat and policy editing using React and TypeScript. Strengthened reliability through end-to-end testing, Kubernetes deployment tooling, and observability with Grafana integration. Addressed onboarding friction and compliance by migrating RBAC logic and enabling enterprise-grade role management, ensuring safer automation and streamlined developer workflows.
Overall Statistics
Feature vs Bugs
33%Features
Repository Contributions
90Total
Bugs
45
Commits
90
Features
22
Lines of code
66,442
Activity Months3
Your Network
53 peopleSame Organization
@archestra.ai5
Work History
January 2026
22 Commits • 5 Features
Jan 1, 2026January 2026 (2026-01) – archestra-ai/archestra. Focused on delivering measurable business value through UX improvements, per-tool policy governance, and platform reliability. Key initiatives include chat editing and creation UX enhancements, a comprehensive per-tool policy framework with migration and autoconfigure capabilities, policy UI improvements, and reliability hardening across MCP/tilt flows. These changes reduce onboarding time, strengthen safety of automated tool usage, and provide clearer governance signals for teams. Key features delivered: - Chat Editing UX Improvements: refined hover areas on action buttons, enhanced editing behavior, autofocus, caret placement, and scroll stability to prevent content jumps. - Chat Creation UX Focus: ensured textarea focuses on chat creation to streamline user flow. - Policy Tooling and Migration: introduced per-tool policy schema and data; migrated policies to per-tool context; default permissive policy and per-tool evaluation support. - Policy Context and UI Improvements: added context variables (team id, agent id) and AND condition support in policy UI, with naming/ordering refinements for clarity. - YOLO mode and styling: introduced tool policy YOLO mode with override semantics and related UI styling/wording fixes. - Reliability and UI stability: improved MCP client handling on ping failure, ensured proper Next termination on tilt down, and fixed profile/assign-tools dialogs to avoid unnecessary refreshes. - Policy Logs: fixed editing from logs and ensured proper JSON formatting of tool results in logs. Overall impact and accomplishments: - Accelerated onboarding and safer automation through per-tool governance and clearer policy signals. - Reduced user friction with chat creation and editing, improving adoption and productivity. - Strengthened governance and compliance posture by enabling per-tool policies, contextual evaluation, and more predictable policy outcomes. Technologies/skills demonstrated: - Frontend UX improvements (hover interactions, autofocus, scroll handling) and React-based UI polish. - Policy engine evolution: per-tool policies, context variables, and logical conditions (AND/OR) in UI. - Data migrations and autoconfiguration workflows for policy data. - Platform reliability practices: MCP/tilt handling, Next lifecycle management, and UI stability drills. - Security governance: policy YOLO mode with explicit user-facing warnings and fallback behavior.
22 Commits • 5 Features
Jan 1, 2026January 2026 (2026-01) – archestra-ai/archestra. Focused on delivering measurable business value through UX improvements, per-tool policy governance, and platform reliability. Key initiatives include chat editing and creation UX enhancements, a comprehensive per-tool policy framework with migration and autoconfigure capabilities, policy UI improvements, and reliability hardening across MCP/tilt flows. These changes reduce onboarding time, strengthen safety of automated tool usage, and provide clearer governance signals for teams. Key features delivered: - Chat Editing UX Improvements: refined hover areas on action buttons, enhanced editing behavior, autofocus, caret placement, and scroll stability to prevent content jumps. - Chat Creation UX Focus: ensured textarea focuses on chat creation to streamline user flow. - Policy Tooling and Migration: introduced per-tool policy schema and data; migrated policies to per-tool context; default permissive policy and per-tool evaluation support. - Policy Context and UI Improvements: added context variables (team id, agent id) and AND condition support in policy UI, with naming/ordering refinements for clarity. - YOLO mode and styling: introduced tool policy YOLO mode with override semantics and related UI styling/wording fixes. - Reliability and UI stability: improved MCP client handling on ping failure, ensured proper Next termination on tilt down, and fixed profile/assign-tools dialogs to avoid unnecessary refreshes. - Policy Logs: fixed editing from logs and ensured proper JSON formatting of tool results in logs. Overall impact and accomplishments: - Accelerated onboarding and safer automation through per-tool governance and clearer policy signals. - Reduced user friction with chat creation and editing, improving adoption and productivity. - Strengthened governance and compliance posture by enabling per-tool policies, contextual evaluation, and more predictable policy outcomes. Technologies/skills demonstrated: - Frontend UX improvements (hover interactions, autofocus, scroll handling) and React-based UI polish. - Policy engine evolution: per-tool policies, context variables, and logical conditions (AND/OR) in UI. - Data migrations and autoconfiguration workflows for policy data. - Platform reliability practices: MCP/tilt handling, Next lifecycle management, and UI stability drills. - Security governance: policy YOLO mode with explicit user-facing warnings and fallback behavior.
January 2026
December 2025
35 Commits • 12 Features
Dec 1, 2025December 2025 monthly work summary focusing on key accomplishments across features, bugs, and impact. Delivered significant feature work in optimization rules UI, provider-aware pricing, enterprise RBAC alignment, and MCP tooling, while stabilizing end-to-end MCP flows and enhancing cost control and security. Major improvements in UI/UX, deployment tooling, and monitoring enabled faster iteration, safer deployments, and clearer business value.
December 2025
35 Commits • 12 Features
Dec 1, 2025December 2025 monthly work summary focusing on key accomplishments across features, bugs, and impact. Delivered significant feature work in optimization rules UI, provider-aware pricing, enterprise RBAC alignment, and MCP tooling, while stabilizing end-to-end MCP flows and enhancing cost control and security. Major improvements in UI/UX, deployment tooling, and monitoring enabled faster iteration, safer deployments, and clearer business value.
November 2025
33 Commits • 5 Features
Nov 1, 2025November 2025 performance summary for archestra-ai/archestra focused on security hardening, reliability, cost efficiency, and tooling improvements. Key delivery highlights include autogenerating ARCHESTRA_AUTH secrets in Helm and Dockerfile with an override path, security hardening of MCP proxy authentication (removing bypass) and removal of internal JWT, a basic LLM cost optimization framework with per-agent toggle and token-based rules (with cost visibility in logs), streamlining tooling provisioning via a bulk MCP tool-to-agent assignment endpoint and seeding MCP tools, and notable observability/maintenance improvements including blocked-tool call metrics and a critical Go CVE patch. Onboarding issues were temporarily disabled to stabilize the release while UI and policy hardening continued (RBAC in chat, prompt safety enhancements, and improved runtime config getters).
33 Commits • 5 Features
Nov 1, 2025November 2025 performance summary for archestra-ai/archestra focused on security hardening, reliability, cost efficiency, and tooling improvements. Key delivery highlights include autogenerating ARCHESTRA_AUTH secrets in Helm and Dockerfile with an override path, security hardening of MCP proxy authentication (removing bypass) and removal of internal JWT, a basic LLM cost optimization framework with per-agent toggle and token-based rules (with cost visibility in logs), streamlining tooling provisioning via a bulk MCP tool-to-agent assignment endpoint and seeding MCP tools, and notable observability/maintenance improvements including blocked-tool call metrics and a critical Go CVE patch. Onboarding issues were temporarily disabled to stabilize the release while UI and policy hardening continued (RBAC in chat, prompt safety enhancements, and improved runtime config getters).
November 2025
Activity
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Quality Metrics
Correctness93.6%
Maintainability84.6%
Architecture86.4%
Performance85.4%
AI Usage36.0%
Skills & Technologies
Programming Languages
BashDockerfileJSONJavaScriptMarkdownPythonSQLShellTypeScriptYAML
Technical Skills
API DevelopmentAPI designAPI developmentAPI integrationBackend DevelopmentCI/CDCloud InfrastructureContainerizationContinuous IntegrationData ModelingDevOpsDockerGrafanaGrafana integrationHelm
Repositories Contributed To
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