style(no-slop): remove every em-dash + banned words across all modules + capstone

Apply the no-ai-slop standard (now binding in AGENTS.md): the em-dash character is
banned outright (restructured, not blind-replaced), plus the banned word/phrase
list (delve, leverage, robust, seamless, truly, unlock, etc.). 0 em-dashes remain
in modules + capstone; the only "robust" left is the planted M10 ai-change.patch
trap. Module H1 titles use a colon separator.

All deliberate teaching devices preserved; labs compile/parse (py/sh/yaml/json);
no junk. AGENTS.md updated with the hard no-slop rules.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01TfzV5QvtPDz8LJS3Pu5VLT

modules/24-assistive-agents/lab/triage.py

@@ -1,14 +1,14 @@
-"""Assistive issue-triage agent — local simulation of a triage bot.
+"""Assistive issue-triage agent: local simulation of a triage bot.
 
 Stands in for a forge-native triage agent (triggered when an issue opens) without a hosted account.
-It assembles the prompt, then validates and renders the AI's suggestion — and stops at a human
+It assembles the prompt, then validates and renders the AI's suggestion, and stops at a human
 confirm. The agent proposes labels and a route; it does not apply them.
 
     python triage.py prompt                          # taxonomy + issue -> prompt for the agent
     python triage.py apply ai-triage.sample.json     # validate + render + confirm gate
 
 The validation step matters: the agent may only use labels that exist in label-taxonomy.md. A
-hallucinated label is rejected. Stdlib only — no pip install.
+hallucinated label is rejected. Stdlib only, no pip install.
 """
 
 import argparse
@@ -31,7 +31,7 @@ and a rationale for the issue that follows. Return ONLY the JSON object the taxo
 """
 
 # Allowed labels are the backticked `prefix:value` tokens in the taxonomy file. Keeping the source
-# of truth in the committed markdown — not hardcoded here — is the point.
+# of truth in the committed markdown (not hardcoded here) is the point.
 LABEL_RE = re.compile(r"`([a-z]+:[a-z0-9-]+)`")
 
 
@@ -75,7 +75,7 @@ def cmd_apply(args: argparse.Namespace) -> int:
     bogus = [l for l in labels if l not in allowed]
     if bogus:
         print("=" * 70)
-        print("REJECTED — the agent suggested labels that aren't in the taxonomy:")
+        print("REJECTED: the agent suggested labels that aren't in the taxonomy:")
         for l in bogus:
             print(f"  - {l}")
         print(
@@ -85,7 +85,7 @@ def cmd_apply(args: argparse.Namespace) -> int:
         return 1
 
     print("=" * 70)
-    print("TRIAGE AGENT — suggestion (advisory only)")
+    print("TRIAGE AGENT: suggestion (advisory only)")
     print("=" * 70)
     print(f"\n  Labels:        {', '.join(labels) or '(none)'}")
     print(f"  Route to:      {sug.get('assignee_type', '?')}")
@@ -99,7 +99,7 @@ def cmd_apply(args: argparse.Namespace) -> int:
         "  - confirm   apply the labels and route as proposed\n"
         "  - edit      change a label or the route, then apply\n"
         "  - reject    the triage is wrong; do it yourself\n"
-        "\nA wrong label here costs one glance and one click to fix — which is exactly why\n"
+        "\nA wrong label here costs one glance and one click to fix, which is exactly why\n"
         "triage is the safe place to let an agent in first.\n"
     )
     return 0