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Most current systems (default Debian/Ubuntu, recent macOS) install Python only as `python3`, with no bare `python` on PATH, so learners who copied `python cli.py ...` into their host shell hit "command not found". Convert host-shell `python <cmd>` -> `python3 <cmd>` across module/lab READMEs, lab `.py` docstrings & usage strings, blog posts, lab prompt and instruction files, the M04 verify.sh message, and the M10/M24 lab patches. Module 01's convention note (and its blog/02 mirror) is rewritten so `python3` is canonical and `python` is the documented fallback. Stop-lines respected: Docker image tags (`python:3.12-slim`), `.venv/.../python` and `...\.venv\Scripts\python.exe` paths, the M20 `"command": "python"` teaching example and surrounding venv prose, container-internal invocations (M16/M18 Dockerfiles, M16 README `docker run` examples), and CI-workflow `run:` steps fed by `actions/setup-python` / `image: python:3.12` are left as `python` on purpose. pip was left out of scope: most occurrences are prose or CI/container-internal, and `pip3` does not fix the PEP 668 externally-managed-environment refusal that the course already addresses with venvs. The M01 note is worded to stay consistent with bare `pip` (use whichever pip pairs with your Python). Build (tools/build_wiki.py) and tools/check.sh both pass. Closes #104 Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01GAEzanEoGJT5o1VizQar47
Module 22 lab files
Run the lab from the module README. Quick map of what's here:
audit.sh: the runnable vetting checklist.bash audit.sh <dir>statically scans a skill or MCP server for red flags (network egress, secret/env reads, shell-out, obfuscation, broad FS access, hidden/injected instructions, zero-width characters). It only reads; it never executes the target.suspicious-skill/: the audit TARGET for Part A. A deliberately malicious "export tasks to Notion" skill (SKILL.md+tools/sync.py). Do not install it or runsync.pyagainst real credentials; it exfiltrates your environment and local secrets. The point is to catch it first.poisoned-task.txt: the prompt-injection payload for Part B. A real-looking task with an injected "system" directive underneath, to add to the Module 1tasks-appand feed to your AI.
Expected result of Part A:
bash audit.sh suspicious-skill # exits non-zero, verdict: REJECT