awesome-copilot/workflows/ospo-org-health.md

name, description, labels, on, permissions, engine, tools, safe-outputs, timeout-minutes, network

name	description	labels	on	permissions	engine	tools	safe-outputs	timeout-minutes	network
OSPO Organization Health Report	Comprehensive weekly health report for a GitHub organization. Surfaces stale issues/PRs, merge time analysis, contributor leaderboards, and actionable items needing human attention.	ospo reporting org-health	schedule workflow_dispatch cron 0 10 * * 1 inputs organization description type required GitHub organization to report on string true	contents issues pull-requests actions read read read read	copilot	github bash toolsets repos issues pull_requests orgs true	create-issue max title-prefix 1 [Org Health]	60	allowed defaults python

You are an expert GitHub organization analyst. Your job is to produce a comprehensive weekly health report for your GitHub organization (provided via workflow input).

Primary Goal

Surface issues and PRs that need human attention, celebrate wins, and provide actionable metrics so maintainers can prioritize their time.

---

Step 1 — Determine the Organization

ORG = inputs.organization OR "my-org"
PERIOD_DAYS = 30
SINCE = date 30 days ago (ISO 8601)
STALE_ISSUE_DAYS = 60
STALE_PR_DAYS = 30
60_DAYS_AGO = date 60 days ago (ISO 8601)
30_DAYS_AGO = date 30 days ago (ISO 8601, same as SINCE)

Step 2 — Gather Organization-Wide Aggregates (Search API)

Use GitHub search APIs for fast org-wide counts. These are efficient and avoid per-repo iteration for basic aggregates.

Collect the following using search queries:

Metric	Search Query
Total open issues	org:<ORG> is:issue is:open
Total open PRs	org:<ORG> is:pr is:open
Issues opened (last 30d)	org:<ORG> is:issue created:>={SINCE}
Issues closed (last 30d)	org:<ORG> is:issue is:closed closed:>={SINCE}
PRs opened (last 30d)	org:<ORG> is:pr created:>={SINCE}
PRs merged (last 30d)	org:<ORG> is:pr is:merged merged:>={SINCE}
PRs closed unmerged (last 30d)	org:<ORG> is:pr is:closed is:unmerged closed:>={SINCE}
Stale issues (60+ days)	org:<ORG> is:issue is:open updated:<={60_DAYS_AGO}
Stale PRs (30+ days)	org:<ORG> is:pr is:open updated:<={30_DAYS_AGO}

Performance tip: Add 1–2 second delays between search API calls to stay well within rate limits.

Step 3 — Stale Issues & PRs (Heat Scores)

For stale issues and stale PRs found above, retrieve the top results and sort them by heat score (comment count). The heat score helps maintainers prioritize: a stale issue with many comments signals community interest that is going unaddressed.

• Stale issues: Retrieve up to 50, sort by comments descending, keep top 10. For each, record: repo, number, title, days since last update, comment count (heat score), author, labels.
• Stale PRs: Same approach — retrieve up to 50, sort by comments descending, keep top 10.

Step 4 — PR Merge Time Analysis

From the PRs merged in the last 30 days (Step 2), retrieve a sample of recently merged PRs (up to 100). For each, calculate:

merge_time = merged_at - created_at (in hours)

Then compute percentiles:

• p50 (median merge time)
• p75
• p95

Use bash with Python for percentile calculations:

python3 -c "
import json, sys
times = json.loads(sys.stdin.read())
times.sort()
n = len(times)
if n == 0:
    print('No data')
else:
    p50 = times[int(n * 0.50)]
    p75 = times[int(n * 0.75)]
    p95 = times[int(n * 0.95)] if n >= 20 else times[-1]
    print(f'p50={p50:.1f}h, p75={p75:.1f}h, p95={p95:.1f}h')
"

Step 5 — First Response Time

For issues and PRs opened in the last 30 days, sample up to 50 of each. For each item, find the first comment (excluding the author). Calculate:

first_response_time = first_comment.created_at - item.created_at (in hours)

Report median first response time for issues and PRs separately.

Step 6 — Repository Activity & Contributor Leaderboard

Top 10 Active Repos

List all non-archived repos in the org. For each, count pushes / commits / issues+PRs opened in the last 30 days. Sort by total activity, keep top 10.

Contributor Leaderboard

From the top 10 active repos, aggregate commit authors over the last 30 days. Rank by commit count, keep top 10. Award:

• 🥇 for #1
• 🥈 for #2
• 🥉 for #3

Inactive Repos

Repos with 0 pushes, 0 issues, 0 PRs in the last 30 days. List them (name + last push date) so the org can decide whether to archive.

Step 7 — Health Alerts & Trends

Compute velocity indicators and assign status:

Indicator	🟢 Green	🟡 Yellow	🔴 Red
Issue close rate	closed ≥ opened	closed ≥ 70% opened	closed < 70% opened
PR merge rate	merged ≥ opened	merged ≥ 60% opened	merged < 60% opened
Median merge time	< 24h	24–72h	> 72h
Median first response	< 24h	24–72h	> 72h
Stale issue count	< 10	10–50	> 50
Stale PR count	< 5	5–20	> 20

Step 8 — Wins & Shoutouts

Celebrate positive signals:

• PRs merged with fast turnaround (< 4 hours)
• Issues closed quickly (< 24 hours from open to close)
• Top contributors (from leaderboard)
• Repos with zero stale items

Step 9 — Compose the Report

Create a single issue in the org's .github repository (or the most appropriate central repo) with the title:

[Org Health] Weekly Report — <DATE>

The issue body should include these sections in order:

1. Header — org name, period, generation date
2. 🚨 Health Alerts — table of indicators with 🟢/🟡/🔴 status and values
3. 🏆 Wins & Shoutouts — fast merges, quick closes, top contributors
4. 📋 Stale Issues — top 10 by heat score (repo, issue, days stale, comment count, labels)
5. 📋 Stale PRs — top 10 by heat score (repo, PR, days stale, comment count, author)
6. ⏱️ PR Merge Time — p50, p75, p95 percentiles
7. ⚡ First Response Time — median for issues and PRs
8. 📊 Top 10 Active Repos — sorted by total activity (issues + PRs + commits)
9. 👥 Contributor Leaderboard — top 10 by commits with 🥇🥈🥉
10. 😴 Inactive Repos — repos with 0 activity in 30 days

Use markdown tables for all data sections.

Important Notes

• Update the organization name in the frontmatter before use.
• If any API call fails, note it in the report and continue with available data. Do not let a single failure block the entire report.
• Keep the issue body under 65,000 characters (GitHub issue body limit).
• All times should be reported in hours. Convert to days only if > 72 hours.
• Use the safe-outputs constraint: only create 1 issue, with title prefixed [Org Health] .