Jira: EGU-3216 · Team Nova

Status: In Progress

Overview

As a developer, having a consistent, AI-assisted way to move through the software development lifecycle, from picking up a Jira story to raising a pull request, reduces manual effort and keeps delivery consistent across projects. This initiative delivers a set of Claude Skills covering story kickoff, technical planning, implementation, code review, validation, and pull request preparation, plus an observability layer so skill usage is actually visible rather than self-reported.

The skill set is shared across two codebases — EGU Partner Portal (EGZP) and EGU Self Service Portal (SSP) — and kept in sync between them.

Approach

The skill set was built iteratively rather than delivered as one drop:

What's Available Today

The following 15 skills live under .claude/skills/ in both the Partner Portal and Self Service Portal repositories, kept in sync between the two.

Story kickoff & planning

Implementation

Review & verification

Delivery

End-to-end orchestration

Observability — Usage Tracking with Langfuse

Claude Code emits OpenTelemetry (OTLP) telemetry. Because the team's self-hosted Langfuse instance runs v2 (which has no native OTLP support), a lightweight proxy (otel-langfuse-proxy, an Azure Container App) bridges the two protocols. It also handles multi-tenant routing — each project's traces land in its own Langfuse project based on a project.id set in that repo's .claude/settings.json, so multiple repositories can share one proxy deployment without their data mixing. Skill and subagent names are read natively from OTEL span attributes, giving accurate trace naming and an automatic skill_invoked score per trace.

The full architecture, setup steps for onboarding a new project, and a record of issues investigated and fixed (including a pricing_tier_id schema issue that was blocking model-cost configuration) are maintained as a living document in both repositories, with the SSP repository containing the latest version:

References