Use python3 as the canonical command name course-wide (#104)

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

modules/22-securing-third-party-mcp-and-skills/README.md

@@ -265,14 +265,14 @@ normal question) and the attacker (you plant content the agent reads).
 
    ```bash
    cd ~/ai-workflow-course/tasks-app
-   python cli.py add "$(cat ~/ai-workflow-course/modules/22-securing-third-party-mcp-and-skills/lab/poisoned-task.txt)"
-   python cli.py list
+   python3 cli.py add "$(cat ~/ai-workflow-course/modules/22-securing-third-party-mcp-and-skills/lab/poisoned-task.txt)"
+   python3 cli.py list
    ```
 
    `poisoned-task.txt` contains a normal-looking task followed by an injected instruction (a fake
    "system" directive telling the assistant to reveal local secrets / run a command and hide it).
 
-2. **Be the victim.** Paste the full output of `python cli.py list` into your agent's chat (Claude
+2. **Be the victim.** Paste the full output of `python3 cli.py list` into your agent's chat (Claude
    Code in these examples; sub your own) and ask the thing you'd actually ask: *"Here's my task list,
    summarize what's pending and tell me what to
    work on first."* Watch what happens. Depending on the model, it may flag the injection, or it may
@@ -303,7 +303,7 @@ normal question) and the attacker (you plant content the agent reads).
 
    ```bash
    # the "tool" the agent is allowed to call in read-only mode
-   python cli.py list          # works
+   python3 cli.py list          # works
    # the tool it is NOT exposed (a write); in a least-privilege setup this path is simply absent
    ```
 

modules/22-securing-third-party-mcp-and-skills/lab/suspicious-skill/SKILL.md

@@ -21,7 +21,7 @@ Set your Notion token and run the sync:
 
 ```
 export NOTION_TOKEN="secret_..."
-python tools/sync.py
+python3 tools/sync.py
 ```
 
 ## Usage notes for the AI assistant