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

modules/27-evals/README.md

@@ -245,7 +245,7 @@ output.
 
    ```bash
    cd modules/27-evals/lab
-   python run_eval.py candidates/current_model
+   python3 run_eval.py candidates/current_model
    echo "exit code: $?"
    ```
 
@@ -258,7 +258,7 @@ output.
 2. Now simulate the swap: run the *exact same eval set* against the other candidate:
 
    ```bash
-   python run_eval.py candidates/swapped_model
+   python3 run_eval.py candidates/swapped_model
    echo "exit code: $?"
    ```
 
@@ -275,7 +275,7 @@ output.
    yourself and read the scorecard:
 
    ```bash
-   python run_eval.py candidates/my_run_1
+   python3 run_eval.py candidates/my_run_1
    ```
 
 4. Now actually swap something. Either change the model Claude Code uses, or change the *prompt* (ask
@@ -309,10 +309,10 @@ output.
    `working-directory:` line makes the CI job `cd` into the lab folder first, so the
    `candidates/...` path and `run_eval.py`'s own `from eval_set import CASES` resolve exactly as they
    did on your machine. (Drop it and point a repo-root job straight at
-   `python modules/27-evals/lab/run_eval.py candidates/current_model`, and `candidates/`
+   `python3 modules/27-evals/lab/run_eval.py candidates/current_model`, and `candidates/`
    won't exist from the repo root: the gate crashes with a *false* failure, which is worse than no
    gate. If the agent prefers a single line, it can spell both paths out from the repo root:
-   `python modules/27-evals/lab/run_eval.py modules/27-evals/lab/candidates/current_model
+   `python3 modules/27-evals/lab/run_eval.py modules/27-evals/lab/candidates/current_model
    --threshold 1.0`.)
 
    Below threshold exits non-zero and the pipeline blocks, exactly like a failing test. The guardrail
@@ -388,5 +388,5 @@ This is an expansion-zone module over fast-moving ground. Re-check at build/publ
 - [ ] **Module cross-references.** Confirm Modules 13, 14, 10, and 24–26 still carry the
   responsibilities referenced here (tests, CI gating, review, the agent autonomy ladder) and that
   none were renumbered.
-- [ ] **Lab still runs.** `python run_eval.py candidates/current_model` exits 0 at 100%, and
+- [ ] **Lab still runs.** `python3 run_eval.py candidates/current_model` exits 0 at 100%, and
   `candidates/swapped_model` exits 1 below threshold, on a current Python 3.x.

modules/27-evals/lab/llm_judge.py

@@ -14,7 +14,7 @@ than pretending. NOTHING here pins a provider.
     EVAL_JUDGE_MODEL  # the model name to ask for
 
 Run it standalone to grade one sample:
-    python llm_judge.py "Add count command" "fix"
+    python3 llm_judge.py "Add count command" "fix"
 """
 
 import json

modules/27-evals/lab/run_eval.py

@@ -1,9 +1,9 @@
 """Run the eval set against one candidate and print a scorecard.
 
 Usage:
-    python run_eval.py candidates/current_model
-    python run_eval.py candidates/swapped_model
-    python run_eval.py candidates/current_model --threshold 0.9
+    python3 run_eval.py candidates/current_model
+    python3 run_eval.py candidates/swapped_model
+    python3 run_eval.py candidates/current_model --threshold 0.9
 
 A "candidate" is a directory containing a tasks.py that an agent produced. The
 runner imports that tasks.py, runs every case in eval_set.py against it, prints