Dora Metrics Reviewer
by Julian
Benchmark your DevOps performance against DORA standards and generate a prioritized 90-day improvement roadmap.
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You say
3-person startup. We deploy to production maybe 2–3 times per week. Lead time from branch to prod is about 3 days on average. Change failure rate is rough — maybe 25%? Things break in prod about 1 in 4 deploys. MTTR is around 3–4 hours.
Your agent does
DORA METRICS REPORT ════════════════════════════════════════ Team: 3-person startup Period: Current (self-reported estimate) Overall Tier: MEDIUM ════════════════════════════════════════
METRIC BREAKDOWN ────────────────────────────────────────────────────── Metric Current Tier vs. Elite Deployment Frequency 2–3×/week HIGH Elite = multiple/day Lead Time for Changes ~3 days HIGH Elite = < 1 hour Change Failure Rate ~25% MEDIUM Elite = 0–15% Mean Time to Restore 3–4 hours HIGH Elite = < 1 hour ──────────────────────────────────────────────────────
BOTTLENECK: Change Failure Rate — at 25%, roughly 1 in 4 deployments causes a production incident. This is dragging the overall tier to MEDIUM and inflating MTTR. Until failure rate drops, increasing deployment frequency will only multiply incidents.
IMPROVEMENT ROADMAP ────────────────────────────────────────────────────── Priority 1: Change Failure Rate (MEDIUM → HIGH) Current: ~25% Target: < 15% (moves from MEDIUM to HIGH/Elite boundary) [... abbreviated ...]
What you get
About this skill
Measure and Accelerate Software Delivery Performance
The DORA Metrics Reviewer is a specialized diagnostic skill designed for engineering leads and DevOps practitioners. Based on the industry-standard DevOps Research and Assessment (DORA) framework, it transforms raw team data into a strategic 90-day execution plan.
What it does
This skill goes beyond simple calculation. It benchmarks your team across the four key metrics: Deployment Frequency, Lead Time for Changes, Change Failure Rate, and Mean Time to Restore (MTTR). It identifies your delivery tier (Elite, High, Medium, or Low) based on the latest research and provides:
- Bottleneck Identification: Pinpoints the specific metric acting as a "binding constraint" on your team's velocity.
- Outlier Analysis: Explains how a single low-performing metric impacts your overall delivery stability.
- Actionable Roadmaps: Generates concrete, technical tasks—like implementing feature flags or trunk-based development—to move you to the next performance tier.
Why use this skill?
Prompting a generic AI for DevOps advice often leads to vague suggestions like "communicate better." This skill enforces high-leverage engineering practices and follows a strict hierarchical logic: for example, prioritizing Lead Time to unlock Deployment Frequency. The output follows a professional, standardized report format ready for stakeholder review.
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
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