Claude-code-ultimate-guide git-ai-archaeology
Analyze AI config evolution in a git repo — first commits per path, monthly distribution, major PRs, maturity phases
git clone https://github.com/FlorianBruniaux/claude-code-ultimate-guide
T=$(mktemp -d) && git clone --depth=1 https://github.com/FlorianBruniaux/claude-code-ultimate-guide "$T" && mkdir -p ~/.claude/skills && cp -r "$T/examples/skills/git-ai-archaeology" ~/.claude/skills/florianbruniaux-claude-code-ultimate-guide-git-ai-archaeology && rm -rf "$T"
examples/skills/git-ai-archaeology/SKILL.mdgit-ai-archaeology
Produces a complete analysis of AI config evolution in a git repository. Finds when each AI configuration file was created, how AI-config commit velocity evolved month by month, which PRs structured the evolution, and identifies maturity phases.
Output: a single file
{output_dir}/{slug}-git-archaeology.md
Expected Input
/git-ai-archaeology repo_path=/path/to/repo [output=./talks/slug] [slug=talk-name] [since=2025-01-01]
: absolute path to the target git repo (required)repo_path
: output directory (default:output
)./talks
: output filename (default: repo folder name)slug
: analysis start date (default: first repo commit)since
Workflow
- Verify the repo: ensure the path exists and is a git repo
- Global metrics: total commits, releases, contributors, time period
- Section 1 — First commits: find creation date for key AI-config paths
- Section 2 — Monthly distribution: commits filtered by AI-config keywords
- Section 3 — Major PRs: extract and categorize significant AI-config commits
- Section 4 — CHANGELOG: if CHANGELOG.md exists, extract releases with AI mentions
- Section 5 — Phases: synthesize evolution phases
- Save the output file
Step 1: Verification and Global Metrics
# Verify it's a git repo git -C {repo_path} rev-parse --git-dir # Global metrics git -C {repo_path} log --oneline | wc -l # total commits git -C {repo_path} tag --sort=version:refname | wc -l # total releases git -C {repo_path} shortlog -sn --no-merges | wc -l # contributors git -C {repo_path} log --pretty=format:"%ad" --date=short | tail -1 # first commit git -C {repo_path} log --pretty=format:"%ad" --date=short | head -1 # last commit git -C {repo_path} log --merges --oneline | wc -l # merged PRs
Step 2: Section 1 — First Commits per AI-Config Path
For each path, find the origin commit with
--diff-filter=A:
# Paths to analyze — adapt based on what exists in the repo PATHS=( "CLAUDE.md" ".claude" ".claude/commands" ".claude/agents" ".claude/hooks" ".claude/skills" ".claude/rules" ".agents" ".cursor" "doc/knowledge-base.md" "doc/guides/ai-instructions" "doc/guides/ai-review" ) for path in "${PATHS[@]}"; do git -C {repo_path} log --diff-filter=A --follow \ --format="%ad | %H | %s" --date=short \ -- "$path" | tail -1 done
Build the Section 1 table from results. Skip paths with no output (don't exist in this repo).
Also build the ASCII timeline:
{date} ─── {path} ─── {message}
Sorted chronologically.
Step 3: Section 2 — Monthly Distribution of AI-Config Commits
Filter commits by AI-config-related keywords:
# All commits with AI-config keywords git -C {repo_path} log --format="%H %s" | \ grep -iE "(claude|feat.ai|docs.ai|tech.ai|mcp|skill|hook|agent|llm|prompt)" \ > /tmp/ai_commits_filtered.txt # Count AI-config commits per month git -C {repo_path} log --format="%ad %H" --date=format:"%Y-%m" | \ while read month hash; do if grep -q "$hash" /tmp/ai_commits_filtered.txt; then echo "$month" fi done | sort | uniq -c
More direct alternative:
git -C {repo_path} log --format="%ad %s" --date=format:"%Y-%m" | \ grep -iE " (feat|fix|docs|tech|chore|refactor)\(ai\)|claude|mcp.*server|\.claude/|skill|hook.*security|guardrail" | \ awk '{print $1}' | sort | uniq -c
Compute per month:
- AI-config commit count
- % of monthly total (cross-reference with all-category monthly total)
- Context (if notable period)
Build ASCII distribution chart (horizontal or vertical bars).
Step 4: Section 3 — Major PRs and Commits
3.1 — feat(ai): / docs(ai): / tech(ai): commits
git -C {repo_path} log --format="%ad | %H | %s" --date=short | \ grep -iE "\(ai\)|\(mcp\)|\[ai\]"
3.2 — MCP Server integrations
git -C {repo_path} log --format="%ad | %H | %s" --date=short | \ grep -iE "mcp|serena|grepai|perplexity|sonar|postgres.*mcp|cursor.*mcp"
3.3 — Skills, commands, hooks, agents
git -C {repo_path} log --format="%ad | %H | %s" --date=short | \ grep -iE "feat\(skill|feat\(hook|feat\(agent|feat\(command|feat\(dx\)|feat\(ci\)" | \ grep -v "^$"
3.4 — Code review automation
git -C {repo_path} log --format="%ad | %H | %s" --date=short | \ grep -iE "review|code-review|pr.*auto|ci.*review"
Step 5: Section 4 — CHANGELOG Analysis (if available)
# Check if CHANGELOG.md exists ls {repo_path}/CHANGELOG.md # Extract releases with AI mentions grep -n "## \[" {repo_path}/CHANGELOG.md | head -30
Read the CHANGELOG and build a table:
| Release | Date | AI-Related Content |
|---|
Only list releases with AI-config content (CLAUDE.md, MCP, agents, skills, hooks, guardrails, prompts, etc.).
Step 6: Section 5 — Evolution Phases
Analyze collected data and identify maturity phases. Typical pattern:
| Phase | Characteristics | Commits | Label |
|---|---|---|---|
| Phase 1 | Basic config, solo usage, no structure | Low | "Config as Afterthought" |
| Phase 2 | Documentation, knowledge base, first MCP | Growing | "Config as Documentation" |
| Phase 3 | Infrastructure: skills/hooks/rules/MCP stack | Spike | "Config as Infrastructure" |
| Phase 4 | Engineering: tests, CI, guardrails, modules | Dense | "Config as Engineering Practice" |
Adapt phases to what the data actually reveals.
Identify the main inflection point: the month where AI-config commit volume spiked.
Compute the "recent vs historical" ratio (e.g., "81% of AI-config commits in the last 2 months").
Output Format: {slug}-git-archaeology.md
# Git Archaeology — AI Config Evolution: {slug} **Source**: Git history of repo `{repo_path}` ({total_commits}+ commits, {total_releases}+ releases) **Method**: `git log --diff-filter=A` for first commits, filtered monthly distribution, major PRs **Last updated**: {date} --- ## Section 1: First Commit per Key Path | Path | Creation Date | Commit Message | Hash | |------|--------------|----------------|------| {rows} ### Creation Timeline \``` {ascii_timeline} \``` --- ## Section 2: Monthly Distribution of AI-Config Commits | Month | AI-Config Commits | % of Total | Context | |-------|-------------------|-----------|---------| {rows} ### Visualization \``` {ascii_chart} \``` **Inflection**: {insight on the commit spike} --- ## Section 3: Major PRs and Commits Related to AI Tooling ### 3.1 PRs `feat(ai):` / `tech(ai):` / `docs(ai):` | Date | Hash | Message | Impact | |------|------|---------|--------| {rows} ### 3.2 MCP Server Integrations (chronological) | Date | MCP Server | Hash / PR | Role | |------|------------|-----------|------| {rows} ### 3.3 Skills, Commands, Hooks, Agents | Date | Hash | Message | Category | |------|------|---------|----------| {rows} ### 3.4 Code Review Automation | Date | Hash | Message | |------|------|---------| {rows} --- ## Section 4: CHANGELOG AI Mentions by Release {section if CHANGELOG available, otherwise "Not applicable"} --- ## Section 5: Evolution Phases ### Evidence-Based Timeline | Milestone | Exact Git Date | Git Evidence | |-----------|----------------|-------------| {rows} ### {N} Evolution Phases #### Phase 1: {Label} ({period}) — {n} commits {description} #### Phase 2: {Label} ({period}) — {n} commits {description} #### Phase 3: {Label} ({period}) — {n} commits {description} #### Phase 4: {Label} ({period}) — {n} commits {description} ### Key Insight {Summary paragraph: main inflection point, recent/historical ratio, what the data reveals about the project's AI maturity.} --- *Generated by git-ai-archaeology — {date}* *Repo: {repo_path} | {total_commits} commits | {total_releases} releases*
Important Rules
- Read-only: no git commands that modify repo state
- Verify before asserting: a date not found in git = note "unverified"
- Adapt paths: Section 1 paths must be filtered to what actually exists in this repo
- Extensible keywords: if the repo uses different conventions (e.g.,
vsfeat[ai]
), adapt grep patternsfeat(ai) - Section 4 optional: if no CHANGELOG.md or no AI mentions, note "Not applicable" and skip to Section 5
- Adaptive phases: 4 phases is a common pattern, not a rule — 2 phases or 6 phases are equally valid
Anti-Patterns
- Inventing data not found in git
- Rounding numbers without flagging it
- Analyzing paths that don't exist in this repo
- Confusing a rename commit with a creation
- Omitting "flat" months (0 AI-config commits also tells a story)
Validation Checklist
- Repo verified and readable
- Section 1: only paths that exist in this repo
- Section 2: distribution covers the full repo period
- Section 3: commits sorted chronologically, hash included
- Section 4: cleanly skipped if no CHANGELOG
- Section 5: phases based on data, not the template
- Output file saved