autology-tutorial by curt-park/autology

Overview

Interactive tutorial in a live git branch. Create real config files, commit them, and watch autology skills trigger naturally.

Duration: ~15 minutes across 3 acts.

Arguments

/autology:autology-tutorial → Start from Act 1
/autology:autology-tutorial <1-3> → Jump to specific act
/autology:autology-tutorial reset → Cleanup (return to original branch, delete tutorial branch, remove tutorial docs)

Setup: Create Tutorial Branch

Check for uncommitted changes first:

git status --short

If clean, create the tutorial branch:

ORIGINAL_BRANCH=$(git rev-parse --abbrev-ref HEAD)
git checkout -b tutorial/autology-demo
echo "Saved original branch: $ORIGINAL_BRANCH"

Tell the user: "We're now on tutorial/autology-demo. All tutorial commits happen here. When we're done, we'll return to $ORIGINAL_BRANCH and delete this branch."

Wait for confirmation before Act 1.

Act 1: Capture — Decision + Code

The scenario: Design a URL shortener. First architectural decision: storage.

Present the technical analysis to the user:

"We're building a URL shortener. The core operation is mapping short codes to original URLs — pure key-value lookups. Here are the options:

Redis: O(1) GET/SET, built-in key expiry (TTL), designed for exactly this pattern

PostgreSQL: relational, flexible — but a full SQL engine for what's essentially a hashmap

In-memory: fastest, but no persistence — data lost on restart"

Use AskUserQuestion:

question: "Which storage would you choose for the URL shortener?"
options:
  - Redis (Recommended) — O(1) lookups, native TTL, built for key-value
  - PostgreSQL — familiar, flexible, but heavier than needed
  - In-memory — fast but no persistence

When user selects Redis, create docker-compose.yml:

services:
  redis:
    image: redis:7-alpine
    ports:
      - "6379:6379"
    volumes:
      - redis_data:/data

volumes:
  redis_data:

Commit:

git add docker-compose.yml
git commit -m "tutorial: add Redis docker-compose"

autology-workflow triggers — commit = trigger point. Now invoke triage then capture for real:

Use Skill tool: autology:triage-knowledge, then autology:capture-knowledge

Triage classifies items, capture creates the doc in docs/ (e.g., docs/tutorial-url-shortener-db.md). After capture completes, stage and commit the newly created doc:

git add docs/tutorial-*.md
git commit -m "tutorial: capture Redis storage decision"

Key insight: Commit introduced a Redis config with no corresponding decision doc. Triage classified it as new → capture created the doc automatically.

> **Autology Tutorial** — Act 1 complete
> Captured: docs/[title-slug].md

Wait for confirmation before Act 2.

Act 2: Sync — Decision Changes

The scenario: New constraint arrives. Discuss, change the code, watch the doc update automatically.

Present the constraint to the user:

"New constraint from infra: Redis is not available in our existing cluster. We'd need to provision it separately — added cost and ops overhead. We do have a PostgreSQL cluster already running."

Use AskUserQuestion:

question: "Given the infra constraint, which alternative would you choose?"
options:
  - PostgreSQL (Recommended) — existing cluster available, no extra infra cost
  - MySQL — similar overhead, team less familiar
  - SQLite — no concurrency, not production-suitable

When user selects PostgreSQL, edit docker-compose.yml to replace Redis with PostgreSQL:

services:
  postgres:
    image: postgres:15-alpine
    environment:
      POSTGRES_DB: urlshortener
      POSTGRES_USER: app
      POSTGRES_PASSWORD: secret
    ports:
      - "5432:5432"
    volumes:
      - pg_data:/var/lib/postgresql/data

volumes:
  pg_data:

Commit:

git add docker-compose.yml
git commit -m "tutorial: switch storage from Redis to PostgreSQL"

autology-workflow triggers — commit = trigger point. Now invoke triage then sync for real:

Use Skill tool: autology:triage-knowledge, then autology:sync-knowledge

Triage identifies the existing doc, sync reads both files, detects the drift, and updates the doc in-place. After sync completes, stage and commit the updated doc:

git add docs/tutorial-*.md
git commit -m "tutorial: sync storage decision (Redis → PostgreSQL)"

Key insight: docker-compose changed to PostgreSQL but the decision doc still said Redis. Triage detected the existing doc, sync updated it in-place to match reality.

> **Autology Tutorial** — Act 2 complete
> Synced: docs/[title-slug].md (Redis → PostgreSQL)

Wait for confirmation before Act 3.

Act 3: Explore — Query the Knowledge Graph

The scenario: Some time has passed. You want to understand the current decision and its rationale.

Use AskUserQuestion:

question: "What would you like to explore in the knowledge base?"
options:
  - "Why did we switch from Redis to PostgreSQL?"
  - "What are the trade-offs of the PostgreSQL choice?"
  - "What alternatives were considered from the start?"

For each selected question:

explore triggers — question about existing knowledge

Use Skill tool: autology:explore-knowledge

Explore will search the knowledge base and answer from the doc content. The node contains:

Why Redis was originally chosen
Why Redis was rejected (infra constraint)
PostgreSQL rationale and trade-offs
Consequences for the team

Point out: this is what explore does in real work — you don't have to remember decisions. The knowledge base answers.

Key insight: Question about existing project knowledge. Explore searches docs/, finds the relevant node, reads it, and answers from captured context.

> **Autology Tutorial** — Act 3 complete

Tutorial Complete

You've seen all three core workflows:

Act	What happened	Skill fired
1: Capture	Redis config committed, no doc existed	triage → capture
2: Sync	Config changed to PostgreSQL, doc said Redis	triage → sync
3: Explore	Asked about the storage decision	explore → answer

The full loop:

code → commit → autology-workflow → triage → capture/sync → commit → explore queries → answer from docs

Cleanup

Return to original branch and remove all tutorial artifacts:

git checkout <ORIGINAL_BRANCH>
git branch -D tutorial/autology-demo

Then remove tutorial docs:

Grep docs/ for frontmatter containing "tutorial" in tags
Delete each matched file with Bash rm

Confirm: "Back on <ORIGINAL_BRANCH>. Tutorial branch deleted. Cleaned up N tutorial nodes."

Next steps:

/autology:triage-knowledge — classify knowledge items after actions
/autology:capture-knowledge — capture knowledge from real conversations
/autology:explore-knowledge — explore graph topology, query decisions and conventions
/autology:sync-knowledge — find doc-code drift anytime (or sync full for complete audit)

Reset Process

When user runs /autology:autology-tutorial reset:

Check current branch — if on tutorial/autology-demo, need to know original branch
git checkout <original-branch>
git branch -D tutorial/autology-demo
Grep docs/ for files with tutorial in tags frontmatter
Delete each with Bash rm
Confirm: "Cleaned up tutorial branch and N tutorial nodes."

Key Principles

Real artifacts: docker-compose is a concrete, tangible file — not just docs
User interaction at each act: user makes decisions, not just watches
Commit → sync: sync always commits the updated doc
Four workflows: triage (classify), capture (new), sync (drift), explore (query)
Guided invocation: the tutorial calls skills explicitly to demonstrate each step — in real work, autology-workflow triggers them automatically after commits