dora-metrics-analysislisted

## What This Skill Does Produces an evidence-based DORA performance analysis for one application or service. It can combine exported data or authorised read-only API results from GitHub, GitLab, Jira, deployment systems, incident systems, and GitHub Copilot metrics. Use Copilot metrics only as contextual adoption data. They cannot calculate DORA metrics on their own and do not establish that Copilot caused a delivery outcome. ## When To Use It - A team wants a DORA baseline, trend analysis, delivery-health review, or improvement experiment. - Available evidence includes production deployments, commits, incidents, recoveries, Jira work items, or GitHub Copilot usage reports. - A user asks to relate delivery performance to AI-tool adoption without asserting unsupported causation. ## Required Evidence Work at the application or service level. Before calculating, declare the measurement window, timezone, service boundary, production-environment definition, source systems, missing fields, and rules for associating commits, deployments, incidents, and recoveries. Request or map these minimum fields: | Dataset | Required fields | | --- | --- | | Deployments | Stable deployment ID, service, environment, completed timestamp, outcome, planned/unplanned status | | Changes | Commit or pull-request ID, service, commit timestamp, linked deployment ID where available | | Incidents | Stable incident ID, affected service, detected and resolved timestamps, linked