commit-archive

name	commit-archive
description	Use when updating, refreshing, or generating the GitHub commit archive (COMMIT_ARCHIVE.md). Handles incremental fetching, analysis of changed repos, and markdown rendering.

Commit Archive

Incrementally update the GitHub commit archive. Scripts handle all API I/O; you analyze only repos with new data.

Workflow

Phase 1: Fetch

bun scripts/src/fetch-commits.ts

Read output. It lists repos with new commits.

Phase 2: Detail

bun scripts/src/fetch-file-changes.ts

Read output. It lists commits that got file-change data.

Phase 3: Analyze

Process repos needing analysis (listed by fetch-commits, most recent first). Skip repos where no new commits arrived since analysis.analyzed_up_to.

For each repo:

1. Read data/commit-archive/repos/{owner}__{name}.json
2. Find new commits (after analysis.analyzed_up_to SHA). Also include a few commits before the cursor as overlap context — work in progress may span across analysis sessions (e.g., a feature started last month, finished this month).
3. Group the visible commits by time period. Analyze each period as a batch — WIP commits together tell the story, not individually.
4. Merge into existing analysis:
   • tech_stack: union (add new, never remove)
   • category: one of the categories below (rarely changes)
   • domain: rarely changes
   • difficulty: 1-5 (can only increase)
   • summary: refine if new work is significant
   • timeline: append new milestones
   • analyzed_up_to: set to newest commit SHA
5. Write updated JSON back

Phase 4: Render

bun scripts/src/render-archive.ts

Phase 5: Verify

Read first 30 and last 30 lines of COMMIT_ARCHIVE.md to confirm.

Categories

Use these exact names for analysis.category:

• Web Applications & Platforms
• Programming Languages & Compilers
• Developer Tools & Libraries
• Desktop Applications & System Tools
• AI/ML & Data Science
• Infrastructure & DevOps
• Game Development
• Korean Language & i18n
• Browser Extensions & Automation
• Mobile Development
• Knowledge Management & Content
• Open Source Contributions (Forks)
• Concepts & Planning-Only Projects
• Bug Reproductions & Test Projects

Difficulty Scale

Value	Label	Criteria
1	Low	README-only, config, single concept
2	Medium	Working app with standard patterns
3	High	Custom architecture, multiple integrations
4	Very High	Novel systems (compilers, AI pipelines, custom frameworks)
5	Extreme	Research-grade, multi-system orchestration