Build a Claude
Code Agent

# Export your OSSA manifest to CLAUDE.md format
ossa export my-agent.ossa.yaml --to claude-md

# Or manually create CLAUDE.md referencing your agent
cat > CLAUDE.md << 'EOF'
# Agent: Code Reviewer

## Role
You are a senior code reviewer specializing in TypeScript and security.

## Tools
- Use the GitLab MCP server for merge request operations
- Use Semgrep for static analysis

## Rules
- Always check for OWASP Top 10 vulnerabilities
- Require tests for any new function
- Follow the project's existing code style
EOF

apiVersion: ossa/v0.5.0
kind: Agent
metadata:
  name: code-reviewer
spec:
  role: Senior code reviewer
  llm:
    provider: anthropic
    model: claude-sonnet-4-6
  tools:
    - name: gitlab-api
      type: mcp
      server:
        command: npx
        args: ["-y", "@anthropic/gitlab-mcp-server"]
    - name: semgrep
      type: mcp
      server:
        command: npx
        args: ["-y", "semgrep-mcp-server"]

{
  "mcpServers": {
    "gitlab": {
      "command": "npx",
      "args": ["-y", "@anthropic/gitlab-mcp-server"],
      "env": {
        "GITLAB_TOKEN": "from-env"
      }
    },
    "ossa-tools": {
      "command": "npx",
      "args": ["-y", "@bluefly/openstandardagents", "mcp", "serve"],
      "env": {
        "AGENT_DIR": ".agents"
      }
    }
  }
}

import Anthropic from '@anthropic-ai/sdk';
import { loadManifest, getTools, getSystemPrompt } from '@bluefly/openstandardagents';

// Load agent definition from OSSA manifest
const manifest = loadManifest('.agents/code-reviewer.ossa.yaml');
const tools = getTools(manifest);        // Converts OSSA tools to Anthropic format
const system = getSystemPrompt(manifest); // Builds system prompt from role + policies

const client = new Anthropic();

async function runAgent(userMessage: string) {
  let messages: Anthropic.MessageParam[] = [
    { role: 'user', content: userMessage }
  ];

  // Agentic loop with tool use
  while (true) {
    const response = await client.messages.create({
      model: manifest.spec.llm.model,
      max_tokens: 4096,
      system,
      tools,
      messages,
    });

    // Check if agent wants to use a tool
    const toolUse = response.content.find(b => b.type === 'tool_use');
    if (!toolUse || response.stop_reason === 'end_turn') {
      return response.content.filter(b => b.type === 'text').map(b => b.text).join('');
    }

    // Execute tool and continue
    const result = await executeTool(toolUse.name, toolUse.input);
    messages.push(
      { role: 'assistant', content: response.content },
      { role: 'user', content: [{ type: 'tool_result', tool_use_id: toolUse.id, content: result }] }
    );
  }
}