Agent skill

archon

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Install this agent skill to your Project

npx add-skill https://github.com/abdullah1854/ClaudeSuperSkills/tree/main/archon

SKILL.md

archon

Visual Kanban board integration with RAG (Retrieval Augmented Generation). Project management with AI-powered context retrieval. Use when: managing tasks visually, integrating project boards, building RAG systems.

Metadata

  • Version: 1.0.0
  • Category: productivity
  • Source: workspace

Tags

kanban, rag, project-management, tasks, retrieval, boards

MCP Dependencies

None specified

Inputs

  • action (string) (required): Action: create-board, add-task, query, sync
  • context (string) (optional): Context for RAG queries or task details
  • board (string) (optional): Board name

Chain of Thought

  1. Initialize board structure. 2. Connect to knowledge base. 3. Enable RAG for smart suggestions. 4. Track task progress. 5. Generate insights from history.

Workflow

No workflow defined

Anti-Hallucination Rules

None specified

Verification Checklist

None specified

Usage

typescript
// Execute via MCP Gateway:
gateway_execute_skill({ name: "archon", inputs: { ... } })

// Or via REST API:
// POST /api/code/skills/archon/execute
// Body: { "inputs": { ... } }

Code

typescript
// Archon - Kanban + RAG Skill
const action = inputs.action || 'create-board';

console.log(\`## Archon: Visual Kanban + RAG

### Action: \${action}

---

## Kanban Board Structure

\`\`\`typescript
interface Board {
  id: string;
  name: string;
  columns: Column[];
  knowledge: KnowledgeBase;
}

interface Column {
  id: string;
  name: string; // "Backlog" | "In Progress" | "Review" | "Done"
  tasks: Task[];
}

interface Task {
  id: string;
  title: string;
  description: string;
  priority: "low" | "medium" | "high";
  labels: string[];
  context: string[]; // RAG-retrieved context
}
\`\`\`

---

## RAG Integration

### Knowledge Base Setup
\`\`\`typescript
// Using vector store for context
const kb = {
  // Store project documentation
  addDocument: async (doc) => {
    const embedding = await embed(doc.content);
    await vectorStore.upsert({
      id: doc.id,
      values: embedding,
      metadata: { source: doc.source, type: doc.type }
    });
  },
  
  // Query relevant context
  query: async (question) => {
    const embedding = await embed(question);
    const results = await vectorStore.query({
      vector: embedding,
      topK: 5
    });
    return results.matches;
  }
};
\`\`\`

### Smart Task Suggestions
\`\`\`typescript
// When creating a task, auto-retrieve relevant context
async function createTask(title, description) {
  // Query knowledge base for relevant docs
  const context = await kb.query(description);
  
  // Suggest related tasks
  const similar = await findSimilarTasks(description);
  
  return {
    title,
    description,
    context: context.map(c => c.metadata.source),
    relatedTasks: similar
  };
}
\`\`\`

---

## Board Operations

### Create Board
\`\`\`bash
# Using TodoWrite for simple Kanban
TodoWrite([
  { content: "Task 1", status: "pending" },    // Backlog
  { content: "Task 2", status: "in_progress" }, // In Progress
  { content: "Task 3", status: "completed" }    // Done
])
\`\`\`

### Sync with External Tools
- Linear: \`linear_*\` MCP tools
- GitHub Projects: \`gh project\` CLI
- Notion: \`notion_*\` MCP tools

---

## RAG Workflow

1. **Index** - Store project docs in vector DB
2. **Query** - Retrieve relevant context for tasks
3. **Augment** - Enhance task descriptions with context
4. **Generate** - AI-powered task breakdown
\`);

Created: Tue Dec 23 2025 00:34:29 GMT+0800 (Singapore Standard Time) Updated: Tue Dec 23 2025 00:34:29 GMT+0800 (Singapore Standard Time)

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