Use python3 as the canonical command name course-wide (#104) (#105)

modules/21-skills-teaching-the-ai-your-playbook/README.md

@@ -87,7 +87,7 @@ This is the distinction to lock in, because the two are siblings and easy to con
 | Analogy | The standing house rules posted on the wall | A labeled recipe card you pull out when you cook that dish |
 
 They're complementary. The instructions file is the right home for facts true *all the time* ("tests
-run with `python -m unittest`"). A skill is the right home for a procedure you run *sometimes* ("here
+run with `python3 -m unittest`"). A skill is the right home for a procedure you run *sometimes* ("here
 is exactly how we add a command"). Module 5 even told you this was coming: start with the always-on
 file; graduate a procedure into a skill when it earns its own page.
 
@@ -147,7 +147,7 @@ On paper this is just "write a runbook." The AI-specific twist is what changes t
 
 - **The AI will execute the playbook, not just read it.** A runbook for a human is a reminder; a skill
   for an agent is something it *performs*. The precision pays off immediately: vague step, vague
-  result; imperative step ("run `python -m unittest`; do not claim success until it's green"), reliable
+  result; imperative step ("run `python3 -m unittest`; do not claim success until it's green"), reliable
   result.
 - **The AI is confidently incomplete without one.** Asked to "add a command," it'll happily stop at
   the code and skip the test, the changelog, the clean commit, and sound finished doing it. The skill
@@ -222,8 +222,8 @@ seen, producing all four parts without you listing the steps.
 5. Watch it perform the procedure. A correctly-followed skill will, without you saying any of it:
    - add `clear()` to `tasks.py` and wire a `clear` branch into `cli.py` (logic in the right file);
    - add a real test to `test_tasks.py` that asserts the list is empty afterward (not just "no crash");
-   - run `python -m unittest` and show it green;
-   - smoke-test `python cli.py clear` and show the output;
+   - run `python3 -m unittest` and show it green;
+   - smoke-test `python3 cli.py clear` and show the output;
    - add a `CHANGELOG.md` line;
    - stage code + test + changelog into one commit, **without** `tasks.json`.
 
@@ -232,8 +232,8 @@ seen, producing all four parts without you listing the steps.
 6. Don't take the AI's word for it. Check against the skill's own done-criteria:
 
    ```bash
-   python -m unittest          # green, and a clear-related test is present
-   python cli.py add "x" && python cli.py clear && python cli.py list   # -> (no tasks yet)
+   python3 -m unittest          # green, and a clear-related test is present
+   python3 cli.py add "x" && python3 cli.py clear && python3 cli.py list   # -> (no tasks yet)
    git show --stat HEAD        # one commit: tasks.py, cli.py, test_tasks.py, CHANGELOG.md; no tasks.json
    ```
 
@@ -318,6 +318,6 @@ time:
       that the example skill format stays generic (when-to-use / inputs / steps / done-criteria).
 - [ ] **Dependency chain intact.** Confirm Module 20 (MCP) and Module 22 (securing servers/skills) are
       still numbered as referenced, and that nothing here leans on a tool introduced after Module 20.
-- [ ] **Lab still runs.** `python -m unittest` is green in `lab/tasks-app/`, and the `clear`-command
+- [ ] **Lab still runs.** `python3 -m unittest` is green in `lab/tasks-app/`, and the `clear`-command
       walkthrough still matches the starter files (`add`/`list`/`done`/`count`, `test_tasks.py`,
       `CHANGELOG.md`).