feat: LLM-powered model auto-configuration and improved onboarding

Major changes:
- Add autoconfigure_models tool for intelligent model assignment
- Implement LLM-based model selection using openclaw agent
- Improve onboarding flow with better model access checks
- Update README with clearer installation and onboarding instructions

Technical improvements:
- Add model-fetcher utility to query authenticated models
- Add smart-model-selector for LLM-driven model assignment
- Use session context for LLM calls during onboarding
- Suppress logging from openclaw models list calls

Documentation:
- Add prerequisites section to README
- Add conversational onboarding example
- Improve quick start flow

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>

lib/tools/setup.ts

@@ -112,9 +112,10 @@ export function createSetupTool(api: OpenClawPluginApi) {
         ...DEV_LEVELS.map((t) => `  dev.${t}: ${result.models.dev[t]}`),
         ...QA_LEVELS.map((t) => `  qa.${t}: ${result.models.qa[t]}`),
         "",
-        "Files:",
-        ...result.filesWritten.map((f) => `  ${f}`),
       );
+
+      lines.push("Files:", ...result.filesWritten.map((f) => `  ${f}`));
+
       if (result.warnings.length > 0)
         lines.push("", "Warnings:", ...result.warnings.map((w) => `  ${w}`));
       lines.push(