alc-dog-training

The Adaptive Learner content repository for Hundetraining (dog training): a Git repository of plain lesson files that the app loads directly and no vendor can lock away.

It ships six German-language knowledge sets (domain dog-training) that form one continuous series on gewaltfreies Training mit positiver Verstärkung (nonviolent training with positive reinforcement), from the very first weeks with a puppy (Teil 0) up to advanced behaviour work (Teil 4). This repository was created from adaptive-learner-content-template, which provides the schema mirror, validator, CI and authoring tooling described below.

Herkunft: Diese Sets lagen zuvor im Test-/Starter-Repo adaptive-learner-content-test (vormals content-test#54 / #65) und wurden in dieses eigenständige Content-Repo verschoben.

The series

Six sets, 23 lessons, source and target language German, content license CC-BY-SA-4.0. Recommended order:

Teil 0: sets/de/welpen-grundkurs (A1, 4 Lektionen)

#	Lesson	Titel
01	01-stubenreinheit.json	Stubenreinheit
02	02-beisshemmung.json	Beißhemmung und Zähnchen
03	03-erste-naechte-ruhe.json	Erste Nächte, Ruhe und Schlaf
04	04-name-bindung-sozialisierung.json	Name, Bindung und erste Sozialisierung

Teil 0+: sets/de/welpen-spezial (A1, 4 Lektionen)

#	Lesson	Titel
01	01-geraeusche-habituation.json	Geräusche und Umweltreize
02	02-ausruestung-angewoehnen.json	Halsband, Geschirr und Leine angewöhnen
03	03-angstphasen.json	Angstphasen ruhig begleiten
04	04-autofahren-ausfluege.json	Autofahren und erste Ausflüge

Teil 1: sets/de/hundetraining-anfaenger (A1, 3 Lektionen)

#	Lesson	Titel
01	01-grundlagen-hundeerziehung.json	Grundlagen der Hundeerziehung
02	02-grundkommandos-sitz-platz.json	Erste Grundkommandos: Sitz und Platz
03	03-rueckruf-leinenfuehrigkeit.json	Rückruf und Leinenführigkeit

Teil 2: sets/de/hundetraining-aufbau (A2, 4 Lektionen)

#	Lesson	Titel
01	01-impulskontrolle-bleib-aus.json	Impulskontrolle: Bleib und Aus
02	02-alleinbleiben.json	Entspannt allein bleiben
03	03-begegnungen-sozialisierung.json	Begegnungen und Sozialisierung
04	04-tricks-beschaeftigung.json	Tricks und Beschäftigung

Teil 3: sets/de/hundetraining-alltag (B1, 4 Lektionen)

#	Lesson	Titel
01	01-antijagdtraining.json	Antijagdtraining
02	02-maulkorbtraining.json	Maulkorbtraining
03	03-medical-training-tierarzt.json	Kooperatives Medical Training
04	04-notrueckruf-ablenkung.json	Notrückruf unter Ablenkung

Teil 4: sets/de/hundetraining-verhalten (B2, 4 Lektionen)

#	Lesson	Titel
01	01-leinenreaktivitaet.json	Leinenreaktivität (Pöbeln an der Leine)
02	02-ressourcenverteidigung.json	Ressourcenverteidigung
03	03-frust-uebererregung.json	Frust und Übererregung
04	04-unsicherheit-selbstvertrauen.json	Unsicherheit und Selbstvertrauen aufbauen

Each lesson combines theory steps with mixed exercise types (matching, cloze, free_text, word_tiles, multiselect; Teil 0+ and Teil 4 also use native multiple_choice). Weiterführende Literatur je Reihenteil steht in books.yaml (domain dog-training).

What's inside

• manifest.yaml: the root manifest listing the six sets above.
• sets/de/<set>/: per set its set manifest plus the lesson JSONs.
• books.yaml: recommended reading for the series (domain dog-training); not a content set, not processed by the validator.
• schema/: the pinned learn-content-engine schema mirror; engine-version.txt holds the pinned engine version and is the source of truth. This is what the content is validated against, independent of the app.
• templates/: starting-point lessons per domain (language / programming / knowledge), kept from the template for authoring new lessons.
• scripts/validate_content.py: the local validator.
• scripts/generate_exercises.py: an optional BYOK AI exercise generator.
• generated/: staging area for AI drafts (never shipped directly).
• .github/workflows/: CI that validates every push/PR against the pinned engine.
• docs/: GETTING-STARTED.md and a local LESSON-FORMAT.md. The canonical, test-validated format reference is the engine's docs/lesson-format.md.

Quick start

git clone https://github.com/astrapi69/alc-dog-training.git
cd alc-dog-training

# Validate all sets (needs only Python 3 + these two deps)
pip install pyyaml jsonschema
python3 scripts/validate_content.py        # exit 0 == all sets pass

Before you push, make lint runs the same semantic engine gate as CI (Engine conformance): it installs the engine release pinned in schema/engine-version.txt into node_modules/ (gitignored; needs Node.js and npm) and checks every lesson and manifest with the engine's rule ids (E-CARD-REF & co.). make lint-warnings additionally prints the engine CLI's warnings (W-*).

Full authoring walkthrough: docs/GETTING-STARTED.md.

Export a set for AI review

scripts/export_set.py writes all lessons of ONE set into a single YAML (or JSON) file so an AI assistant or a human can review the whole set in one pass (syntax, correctness, consistency across lessons):

python3 scripts/export_set.py welpen-grundkurs
# -> exports/welpen-grundkurs-de-<timestamp>.yaml
python3 scripts/export_set.py hundetraining-anfaenger --format json --out /tmp/review.json

The slug is the set id from the root manifest.yaml or the folder name of the set path; when the same folder name exists under several source-language directories, --lang (default de) picks the sets/<lang>/ directory. Umlauts stay real UTF-8. An unknown slug aborts with a list of the available sets. The exports/ folder is gitignored (read-only snapshot, not a re-import format).

Full usage guide: docs/export-set-usage.md (English) / docs/export-set-usage.de.md (Deutsch).

Generate exercises with AI (optional)

scripts/generate_exercises.py turns a topic into a lesson with a BYOK model (Anthropic / OpenAI / Gemini) and gates every draft through validate_content.py before writing it into generated/:

export ANTHROPIC_API_KEY="sk-..."          # or OPENAI_API_KEY / GEMINI_API_KEY
python3 scripts/generate_exercises.py \
  --topic "Rückruf unter Ablenkung aufbauen" \
  --target-lang de --source-lang de --set-id hundetraining-alltag

A draft is a draft until you review it: no validator catches a claim that is factually wrong about dog behaviour or training method.

How it stays current

The content is validated against the pinned engine version in schema/engine-version.txt on every push and pull request (structural + semantic + drift gates in .github/workflows/). A green CI means the content is valid for every consumer of that engine release. When the engine is bumped, it reaches this repository the same way it reaches the rest of the chain: a deliberate pin-bump PR that the drift gate guards.

The tooling is licensed MIT (see LICENSE); the lesson content carries its own license, CC-BY-SA-4.0, declared in each set manifest's metadata.license.