learning-path

name	learning-path
description	Run the local Claude Code learning path, record evidence, and schedule evidence-based reviews.

Claude Code Learning Path

Use this skill to follow a bounded, local progression through the existing seven-module guide. The engine selects only modules whose prerequisites are complete, saves nothing outside the current project's .claude/learning/ directory, requires a non-empty evidence note, and rejects corrupt state.

Start with the diagnostic

Run /self-assessment quick before choosing a track. It is a self-reporting aid, not a certification. Map its result deliberately:

Self-assessment result	Learning-path track
Beginner	Beginner
Intermediate	Practitioner
Advanced	Production

Maintainer is not a self-assessment result. Select it manually only when the goal is shared governance, such as maintaining team instructions, controls, or evidence practices.

Choose the lowest track that covers your immediate goal:

Track	Outcome	Modules
Beginner	Safe first daily workflow	01 to 03
Practitioner	Reusable project workflows	01 to 05
Production	Automation with verification controls	01 to 07
Maintainer	Shared practice and governance	01 to 07

The module definitions, guide references, exercises, prerequisites, and review intervals are in assets/path.yaml. The source curriculum is the existing seven-module learning path.

Commands

Run commands from the repository or project being learned. CLAUDE_SKILL_DIR is the installed-skill directory provided by Claude Code. --root "$PWD" makes the learner's current project, rather than the installed skill, the only state target.

python3 "${CLAUDE_SKILL_DIR}/scripts/progress.py" --root "$PWD" init --track Beginner
python3 "${CLAUDE_SKILL_DIR}/scripts/progress.py" --root "$PWD" status
python3 "${CLAUDE_SKILL_DIR}/scripts/progress.py" --root "$PWD" next
python3 "${CLAUDE_SKILL_DIR}/scripts/progress.py" --root "$PWD" complete module-01 \
  --evidence "Installed Claude Code, ran /help, and recorded the version."
python3 "${CLAUDE_SKILL_DIR}/scripts/progress.py" --root "$PWD" due

The state file is .claude/learning/claude-code-guide-progress.json. It belongs to the learner's project, not this installed skill. init refuses to overwrite an existing state file. Keep the state local unless you deliberately decide to share the evidence.

Completion gate

Before completing a module:

1. Read the linked guide page.
2. Do the linked exercise in a real project.
3. Record a concrete evidence note that another person can inspect, such as a command, changed file, test result, or review artifact.
4. Use next to retrieve the next unlocked module.

An empty note, an unmet prerequisite, an unknown module, a module outside the selected track, or corrupt state is an error. The tool does not infer completion from a percentage, a command exit code, or an assertion by the learner.

Reviews

Each completion schedules reviews exactly at 1, 3, 7, 14, 30, 60, and 90 days after the recorded completion date. due returns all scheduled reviews due on or before today. Revisit the linked exercise and update a separate proof artifact if the knowledge has changed.

Safety boundary

All writes are local and atomic. A malformed state file fails closed and remains untouched for inspection or recovery. The prototype does not call a network service, install packages, assess competence automatically, or edit the guide.

Validation boundary

The runtime validates path.yaml with Python's JSON parser because the file uses the JSON subset of YAML. The bundled quick_validate.py skill validator imports PyYAML before it parses SKILL.md frontmatter. If that import fails, this frontmatter validation is UNKNOWN, not a successful skill validation. The dependency-free runtime tests can still establish that this exact path definition loads.