Skills Development Analyzing AI Adoption History in Git

Analyzing AI Adoption History in Git

v20260730
git-ai-archaeology
This tool performs a comprehensive analysis of AI configuration file evolution within a Git repository. It tracks when specific AI configs were first introduced, charts monthly commit velocity related to AI features, highlights key PRs that shaped the development, and synthesizes the project's AI maturity phases. Ideal for mapping AI adoption timelines and assessing technical maturity.
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Overview

git-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]
  • repo_path: absolute path to the target git repo (required)
  • output: output directory (default: ./talks)
  • slug: output filename (default: repo folder name)
  • since: analysis start date (default: first repo commit)

Workflow

  1. Verify the repo: ensure the path exists and is a git repo
  2. Global metrics: total commits, releases, contributors, time period
  3. Section 1: First commits: find creation date for key AI-config paths
  4. Section 2: Monthly distribution: commits filtered by AI-config keywords
  5. Section 3: Major PRs: extract and categorize significant AI-config commits
  6. Section 4: CHANGELOG: if CHANGELOG.md exists, extract releases with AI mentions
  7. Section 5: Phases: synthesize evolution phases
  8. 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:

ReleaseDateAI-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:

PhaseCharacteristicsCommitsLabel
Phase 1Basic config, solo usage, no structureLow"Config as Afterthought"
Phase 2Documentation, knowledge base, first MCPGrowing"Config as Documentation"
Phase 3Infrastructure: skills/hooks/rules/MCP stackSpike"Config as Infrastructure"
Phase 4Engineering: tests, CI, guardrails, modulesDense"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., feat[ai] vs feat(ai)), adapt grep patterns
  • 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
Info
Category Development
Name git-ai-archaeology
Version v20260730
Size 9.29KB
Updated At 2026-08-04
Language