fix(voice/consistency): vary stock formulas, vendor-balance orient.py, unify the loop

- Vary 11 instances of two boilerplate openers ("A generic X course…" /
  "Strip away X…") across 10 modules so they read as distinct, concrete prose;
  kept the few deliberate, voice-distinct uses; locked exemplars untouched.
- M23 orient.py: detect a vendor-balanced set of AI-instruction filenames
  (AGENTS.md/CLAUDE.md/GEMINI.md/.cursorrules/.cursor/rules/copilot-instructions)
  instead of singling out one vendor. Still runs.
- Render the collaboration loop consistently as seven stations
  (issue->branch->implementation->PR->review->merge->closed) in M25/M26 to match
  M11 and the syllabus.

Closes #48
Closes #49
Closes #51

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

modules/20-mcp-servers-giving-the-ai-hands/README.md

@@ -201,9 +201,9 @@ that same AI hands beyond the repo. The next three modules build directly on it:
 
 ## The AI angle
 
-A generic integration course would teach you to wire systems together for *programs* to use —
-fixed clients calling fixed endpoints. MCP is shaped for a different consumer: **an AI that decides
-at runtime what it needs.** That changes what matters about the integration.
+Most integration work wires systems together for *programs* to use — fixed clients calling fixed
+endpoints. MCP is shaped for a different consumer: **an AI that decides at runtime what it needs.**
+That changes what matters about the integration.
 
 - **Discovery, not hardcoding.** A traditional client is written against specific API calls by a
   human. An MCP client hands the AI a *menu* — tool names, descriptions, argument schemas — and the