upstream-hive

name

upstream-hive

description

Digest a repo by tracing connections — which files move together, which PRs close which issues, who works at what hour. A bee's-eye view of the hive. Merges commits+PRs+issues on one timestamp axis, detects co-change clusters (files that always ship together = hidden coupling), maps contributor rhythm (timezone/hour heatmap), and highlights cause→effect chains (issue opened → PR merged → issue closed). Reruns on any repo. Use to understand "how does this team actually work?" in 30 seconds.

/upstream-hive — ตัวต่อมองรัง 🐝

"ตัวต่อไม่นับดอกไม้ — มันดูว่าดอกไหนเชื่อมกัน เส้นทางไหนมีน้ำหวาน เส้นทางไหนแห้ง"

A repo-digest skill that sees connections, not just counts.

คิดต่าง / ทำให้ดีกว่าตัวอย่างยังไง

Plain digest	/upstream-hive (อันนี้)
Count commits per day	Co-change clusters — ไฟล์ไหนเปลี่ยนพร้อมกันเสมอ = hidden coupling
List PRs merged	Cause→effect chains — issue#X → PR#Y → close ใน N นาที
"229 commits on 06-06"	Rhythm map — ใครทำงานกี่โมง timezone ไหน sprint pattern
Classify by prefix	4-layer digest — timeline + clusters + rhythm + chains

4 Layers

Layer 1: Timeline (timestamp = SSOT)

Merge commits + PRs + issues on one axis, group by day, flag spikes.

Layer 2: Co-change Clusters

For each commit, extract changed files → find file pairs that co-occur ≥3 times → these are the real modules, not what the folder structure says.

Layer 3: Contributor Rhythm

Map commits by hour (Bangkok TZ) → see when the team actually works. Bimodal = night owls + morning people. Spike hours = sync points.

Layer 4: Cause→Effect Chains

Match fixes #N / closes #N in commit/PR messages → trace issue → fix → merge → close timeline. Fastest chain = team velocity signal.

Usage

./digest.sh                           # maw-js, last 14 days
./digest.sh Soul-Brews-Studio/maw-js  # explicit
./digest.sh owner/repo 2026-05-25     # custom since date

Output

Prints 4 sections to stdout + saves full report to OUTPUT.md:

1. Timeline by day (with spike flags)
2. Top co-change clusters (file pairs)
3. Contributor rhythm heatmap
4. Cause→effect chains (issue → PR → close)