chore: move source to repo root and standardize config

Phase 1 — Structural overhaul:
- Move all source from headlamp-sealed-secrets/ subdirectory to repo root
- Delete 23 AI-generated docs, 8 pre-built tarballs, release snapshots dir
- Remove all working-directory refs from CI/release workflows
- Update install-plugin.sh and typedoc.json paths

Phase 2 — Config standardization:
- Create .eslintrc.js and .prettierrc.js (standard Headlamp configs)
- Remove inline eslintConfig/prettier from package.json (drop jsx-a11y, prettier extends)
- Rewrite tsconfig.json (package name extend, add compilerOptions.types)
- Create vitest.config.mts and vitest.setup.ts (standard from polaris)
- Replace headlamp-plugin CLI scripts with direct tool invocation
- Rewrite .gitignore with standard baseline

Phase 3 — MCP & Claude settings:
- Create .mcp.json with github/kubernetes/flux/playwright servers
- Create .claude/settings.local.json
- Remove 7 specialized agents, keep 3 meta-orchestration agents

Phase 4 — Documentation:
- Rewrite CLAUDE.md (remove subdirectory refs, standard format)
- Add ArtifactHub badge, Architecture section, standardized install methods to README.md
- Create CONTRIBUTING.md and SECURITY.md
- Fix pre-existing test bugs in validators.test.ts (isValidNamespace returns boolean,
  not ValidationResult; error message string mismatches)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

.claude/agents/agent-organizer.md

@@ -1,13 +1,12 @@
 ---
 name: agent-organizer
-description: "Use when assembling and optimizing multi-agent teams to execute complex projects that require careful task decomposition, agent capability matching, and workflow coordination."
+description: Use when assembling and optimizing multi-agent teams to execute complex projects that require careful task decomposition, agent capability matching, and workflow coordination.
 tools: Read, Write, Edit, Glob, Grep
 model: sonnet
 ---
 
 You are a senior agent organizer with expertise in assembling and coordinating multi-agent teams. Your focus spans task analysis, agent capability mapping, workflow design, and team optimization with emphasis on selecting the right agents for each task and ensuring efficient collaboration.
 
-
 When invoked:
 1. Query context manager for task requirements and available agents
 2. Review agent capabilities, performance history, and current workload
@@ -284,4 +283,4 @@ Integration with other agents:
 - Partner with knowledge-synthesizer on learning
 - Coordinate with all agents on task execution
 
-Always prioritize optimal agent selection, efficient coordination, and continuous improvement while orchestrating multi-agent teams that deliver exceptional results through synergistic collaboration.
+Always prioritize optimal agent selection, efficient coordination, and continuous improvement while orchestrating multi-agent teams that deliver exceptional results through synergistic collaboration.