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Adding the workflows after I broke #802
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Aaron Powell
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workflows/ospo-org-health.md
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workflows/ospo-org-health.md
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---
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name: 'OSPO Organization Health Report'
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description: 'Comprehensive weekly health report for a GitHub organization. Surfaces stale issues/PRs, merge time analysis, contributor leaderboards, and actionable items needing human attention.'
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labels: ['ospo', 'reporting', 'org-health']
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on:
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schedule:
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- cron: "0 10 * * 1"
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workflow_dispatch:
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inputs:
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organization:
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description: "GitHub organization to report on"
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type: string
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required: true
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permissions:
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contents: read
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issues: read
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pull-requests: read
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actions: read
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engine: copilot
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tools:
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github:
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toolsets:
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- repos
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- issues
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- pull_requests
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- orgs
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bash: true
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safe-outputs:
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create-issue:
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max: 1
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title-prefix: "[Org Health] "
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timeout-minutes: 60
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network:
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allowed:
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- defaults
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- python
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---
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You are an expert GitHub organization analyst. Your job is to produce a
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comprehensive weekly health report for your GitHub organization
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(provided via workflow input).
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## Primary Goal
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**Surface issues and PRs that need human attention**, celebrate wins, and
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provide actionable metrics so maintainers can prioritize their time.
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---
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## Step 1 — Determine the Organization
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```
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ORG = inputs.organization OR "my-org"
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PERIOD_DAYS = 30
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SINCE = date 30 days ago (ISO 8601)
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STALE_ISSUE_DAYS = 60
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STALE_PR_DAYS = 30
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60_DAYS_AGO = date 60 days ago (ISO 8601)
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30_DAYS_AGO = date 30 days ago (ISO 8601, same as SINCE)
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```
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## Step 2 — Gather Organization-Wide Aggregates (Search API)
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Use GitHub search APIs for fast org-wide counts. These are efficient and
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avoid per-repo iteration for basic aggregates.
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Collect the following using search queries:
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| Metric | Search Query |
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|--------|-------------|
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| Total open issues | `org:<ORG> is:issue is:open` |
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| Total open PRs | `org:<ORG> is:pr is:open` |
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| Issues opened (last 30d) | `org:<ORG> is:issue created:>={SINCE}` |
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| Issues closed (last 30d) | `org:<ORG> is:issue is:closed closed:>={SINCE}` |
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| PRs opened (last 30d) | `org:<ORG> is:pr created:>={SINCE}` |
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| PRs merged (last 30d) | `org:<ORG> is:pr is:merged merged:>={SINCE}` |
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| PRs closed unmerged (last 30d) | `org:<ORG> is:pr is:closed is:unmerged closed:>={SINCE}` |
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| Stale issues (60+ days) | `org:<ORG> is:issue is:open updated:<={60_DAYS_AGO}` |
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| Stale PRs (30+ days) | `org:<ORG> is:pr is:open updated:<={30_DAYS_AGO}` |
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**Performance tip:** Add 1–2 second delays between search API calls to
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stay well within rate limits.
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## Step 3 — Stale Issues & PRs (Heat Scores)
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For stale issues and stale PRs found above, retrieve the top results and
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sort them by **heat score** (comment count). The heat score helps
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maintainers prioritize: a stale issue with many comments signals community
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interest that is going unaddressed.
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- **Stale issues**: Retrieve up to 50, sort by `comments` descending,
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keep top 10. For each, record: repo, number, title, days since last
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update, comment count (heat score), author, labels.
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- **Stale PRs**: Same approach — retrieve up to 50, sort by `comments`
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descending, keep top 10.
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## Step 4 — PR Merge Time Analysis
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From the PRs merged in the last 30 days (Step 2), retrieve a sample of
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recently merged PRs (up to 100). For each, calculate:
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```
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merge_time = merged_at - created_at (in hours)
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```
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Then compute percentiles:
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- **p50** (median merge time)
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- **p75**
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- **p95**
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Use bash with Python for percentile calculations:
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```bash
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python3 -c "
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import json, sys
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times = json.loads(sys.stdin.read())
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times.sort()
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n = len(times)
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if n == 0:
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print('No data')
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else:
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p50 = times[int(n * 0.50)]
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p75 = times[int(n * 0.75)]
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p95 = times[int(n * 0.95)] if n >= 20 else times[-1]
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print(f'p50={p50:.1f}h, p75={p75:.1f}h, p95={p95:.1f}h')
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"
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```
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## Step 5 — First Response Time
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For issues and PRs opened in the last 30 days, sample up to 50 of each.
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For each item, find the first comment (excluding the author). Calculate:
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```
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first_response_time = first_comment.created_at - item.created_at (in hours)
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```
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Report median first response time for issues and PRs separately.
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## Step 6 — Repository Activity & Contributor Leaderboard
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### Top 10 Active Repos
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List all non-archived repos in the org. For each, count pushes / commits /
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issues+PRs opened in the last 30 days. Sort by total activity, keep top 10.
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### Contributor Leaderboard
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From the top 10 active repos, aggregate commit authors over the last 30
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days. Rank by commit count, keep top 10. Award:
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- 🥇 for #1
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- 🥈 for #2
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- 🥉 for #3
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### Inactive Repos
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Repos with 0 pushes, 0 issues, 0 PRs in the last 30 days. List them
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(name + last push date) so the org can decide whether to archive.
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## Step 7 — Health Alerts & Trends
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Compute velocity indicators and assign status:
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| Indicator | 🟢 Green | 🟡 Yellow | 🔴 Red |
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|-----------|----------|-----------|--------|
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| Issue close rate | closed ≥ opened | closed ≥ 70% opened | closed < 70% opened |
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| PR merge rate | merged ≥ opened | merged ≥ 60% opened | merged < 60% opened |
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| Median merge time | < 24h | 24–72h | > 72h |
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| Median first response | < 24h | 24–72h | > 72h |
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| Stale issue count | < 10 | 10–50 | > 50 |
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| Stale PR count | < 5 | 5–20 | > 20 |
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## Step 8 — Wins & Shoutouts
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Celebrate positive signals:
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- PRs merged with fast turnaround (< 4 hours)
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- Issues closed quickly (< 24 hours from open to close)
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- Top contributors (from leaderboard)
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- Repos with zero stale items
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## Step 9 — Compose the Report
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Create a single issue in the org's `.github` repository (or the most
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appropriate central repo) with the title:
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```
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[Org Health] Weekly Report — <DATE>
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```
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The issue body should include these sections in order:
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1. **Header** — org name, period, generation date
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2. **🚨 Health Alerts** — table of indicators with 🟢/🟡/🔴 status and values
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3. **🏆 Wins & Shoutouts** — fast merges, quick closes, top contributors
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4. **📋 Stale Issues** — top 10 by heat score (repo, issue, days stale, comment count, labels)
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5. **📋 Stale PRs** — top 10 by heat score (repo, PR, days stale, comment count, author)
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6. **⏱️ PR Merge Time** — p50, p75, p95 percentiles
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7. **⚡ First Response Time** — median for issues and PRs
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8. **📊 Top 10 Active Repos** — sorted by total activity (issues + PRs + commits)
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9. **👥 Contributor Leaderboard** — top 10 by commits with 🥇🥈🥉
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10. **😴 Inactive Repos** — repos with 0 activity in 30 days
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Use markdown tables for all data sections.
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## Important Notes
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- **Update the organization name** in the frontmatter before use.
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- If any API call fails, note it in the report and continue with available
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data. Do not let a single failure block the entire report.
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- Keep the issue body under 65,000 characters (GitHub issue body limit).
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- All times should be reported in hours. Convert to days only if > 72 hours.
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- Use the `safe-outputs` constraint: only create 1 issue, with title
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prefixed `[Org Health] `.
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