dora-report

name	dora-report
description	Generate a DORA-REPORT.md for this repository by computing the five core DORA software delivery performance metrics and three DORA agentic metrics from available data sources. Use this when asked to generate a DORA report or assess delivery performance.
category	metrics
license	MIT
metadata	{"author":"d-oit","version":"1.0"}

Skill: dora-report

When to Use

• User asks for this skill's functionality

Purpose

Generate a DORA-REPORT.md for this repository by computing the five core DORA software delivery performance metrics and three DORA agentic metrics from available data sources.

When to use

• When asked to generate a DORA report or assess delivery performance
• During sprint reviews or quarterly assessments
• When evaluating the ROI of AI tooling adoption
• Run this skill monthly to track trends

Prerequisites

• GitHub CLI (gh) installed and authenticated
• Python 3.9+ available
• .agents/metrics.jsonl exists
• dora-metrics.jsonl exists

Steps

1. Fetch Deployment Frequency data from GitHub API

gh api "/repos/{owner}/{repo}/releases" --paginate \
  --jq '[.[] | {tag: .tag_name, published: .published_at}]' \
  > /tmp/releases.json

2. Fetch PR Lead Time data

gh api "/repos/{owner}/{repo}/pulls?state=closed&base=main" --paginate \
  --jq '[.[] | select(.merged_at != null) | {pr: .number, created: .created_at, merged: .merged_at}]' \
  > /tmp/prs.json

3. Run the compute script

python3 .agents/skills/dora-report/scripts/compute_dora.py \
  --releases /tmp/releases.json \
  --prs /tmp/prs.json \
  --agent-metrics .agents/metrics.jsonl \
  --dora-metrics dora-metrics.jsonl \
  --template .agents/skills/dora-report/templates/DORA-REPORT.md.jinja \
  --output reports/DORA-REPORT.md \
  --period-days 30 \
  --repo $(git remote get-url origin | sed 's/.*github.com[:\/]\(.*\)\.git/\1/')

4. Review and commit the report

git add reports/DORA-REPORT.md
git commit -m "docs(dora): update reports/DORA-REPORT.md [skip ci]"

5. Log the report generation in metrics.jsonl

Append to .agents/metrics.jsonl:

echo '{"timestamp":"'$(date -u +%Y-%m-%dT%H:%M:%SZ)'","agent":"claude","skill":"dora-report","task_description":"Generated monthly DORA report","success":true,"human_interventions":0}' >> .agents/metrics.jsonl

Success Criteria

• reports/DORA-REPORT.md is generated with up-to-date metrics.
• All four core DORA metrics and three agentic metrics are populated.
• The report is committed to the repository.
• The activity is logged in .agents/metrics.jsonl.

Rationalizations

Rationalization	Reality
"We shipped a lot of features, so DORA must be good."	DORA measures flow efficiency, not volume. Ship fast but measure lead time.
"Our MTTR is low because we roll back quickly."	Rollback isn't recovery. Recovery means the fix is deployed and working.
"Manual deployment is fine for our team size."	Manual deployment is the #1 blocker for Deployment Frequency improvement.

Red Flags

• Running DORA report less than monthly (trends need data points)
• Ignoring Lead Time for Changes (the hardest metric to improve)
• Not tracking human_interventions in metrics (hides true agent performance)

GH CLI Usage

Use gh run watch to gate DORA recovery recording on CI passing:

# Find latest CI run for a branch
RUN_ID=$(gh run list --branch hotfix/my-fix --workflow ci.yml \
  --limit 1 --json databaseId --jq '.[0].databaseId')

# Block until CI completes; exits non-zero if CI fails
gh run watch "$RUN_ID" --exit-status

This ensures FDRT recovery is only counted after a verified green build.