CCA Code Generation Scenario Guide: Master Claude Code for the 2026 Exam

Short Answer

The CCA exam code generation scenario tests end-to-end Claude Code workflows including CLAUDE.md configuration, multi-pass code review for large codebases, CI/CD integration, and economic tradeoffs between Claude 4.6 Opus vs. 4.5/4.6 Sonnet models. This scenario comprises 20% of Domain 3 (Claude Code Configuration & Workflows) and appears in 4 of the 6 randomized production scenarios on the 60-question exam.

Understanding the Code Generation Scenario

The code generation scenario is one of six production scenarios that can appear on the CCA exam, specifically testing your ability to design and implement Claude Code workflows at enterprise scale. Unlike basic prompt engineering, this scenario evaluates your understanding of CLAUDE.md as a persistent "tech lead", multi-pass code review strategies, and economic optimization across different Claude model variants.

This scenario directly maps to Domain 3: Claude Code Configuration & Workflows (20% exam weight) and intersects with Domain 1: Agentic Architecture and Orchestration (27% exam weight) when testing orchestration decisions. According to Anthropic's official exam guide, candidates must demonstrate 6+ months of hands-on experience with Claude Code, including production deployments and CI/CD integration.

The scenario presents realistic challenges like reviewing 10,000+ line codebases, maintaining architectural consistency across teams, and optimizing token costs while preserving code quality. Questions test both technical configuration (settings hierarchy, hooks, permissions) and strategic decisions (when to escalate to human review, model selection based on complexity).

Key topics include CLAUDE.md instruction hierarchies, PostToolUse hooks for auto-formatting, permission patterns for safe CI/CD integration, and economic modeling for sustained code generation workloads. The scenario emphasizes production reliability over proof-of-concept implementations.

CLAUDE.md as Your Persistent Tech Lead

The CLAUDE.md system functions as a persistent technical leader that maintains project standards across all Claude Code interactions. This concept is fundamental to the code generation scenario and frequently misunderstood by exam candidates.

markdown# User-level: ~/.claude/CLAUDE.md (global preferences)
# Project-level: ./CLAUDE.md (repository root, version-controlled)
# Directory-level: ./src/CLAUDE.md (module-specific rules)
# Parent directories: walking up from project root (monorepo support)

All files merge rather than override, with lower levels extending higher-level instructions. This enables teams to establish global coding standards while allowing project-specific customizations.

A production-quality CLAUDE.md includes build commands (Claude Code executes these automatically), architecture decisions, coding standards, and critical gotchas. The exam tests your ability to design CLAUDE.md files that prevent common errors like inconsistent naming conventions, architectural violations, and dangerous operations.

markdown# Project: FinanceAPI

## Commands
- Build: `npm run build`
- Test: `npm test -- --coverage`
- Lint: `npm run lint:fix`
- Type check: `npx tsc --noEmit`

## Architecture Rules
- All API routes must use Zod validation
- Database queries only through Prisma ORM
- No direct SQL in application code
- Authentication required for all /api routes except /health

## Critical Constraints
- Never modify src/auth/middleware.ts directly
- PII must be encrypted before database storage
- All financial calculations use decimal.js (never floating point)

Understanding when to place instructions at user, project, or directory levels directly impacts exam scenarios involving team collaboration and monorepo architectures.

Multi-Pass Code Review Strategies

The exam presents scenarios where single-pass review fails due to context window limitations or complexity thresholds. Candidates must design workflows that segment code logically (by module, feature, or dependency graph) while preserving cross-cutting concerns like security patterns and performance optimizations.

The exam tests your ability to coordinate passes effectively, including how to maintain state between passes, when to escalate complex decisions to human architects, and how to validate consistency across pass boundaries. Questions often involve tradeoffs between review thoroughness and economic efficiency.

CI/CD Integration Patterns

json{
  "permissions": {
    "allow": [
      "Bash(npm run build)",
      "Bash(npm test -- --coverage)",
      "Bash(git status)",
      "Bash(git diff *)",
      "Read",
      "Write(src/**)",
      "Edit(src/**/*.ts)"
    ],
    "deny": [
      "Bash(git push *)",
      "Bash(rm -rf *)",
      "Bash(docker *)",
      "Write(.env*)",
      "Edit(package.json)"
    ]
  }
}

The scenario tests your understanding of hook environment variables ($TOOL_NAME, $TOOL_INPUT, $TOOL_OUTPUT) and return code semantics (exit code 2 blocks PreToolUse operations, non-empty Stop hook output continues the loop).

Economic Optimization: Model Selection Strategies

Understanding sustained workload economics is crucial for enterprise deployments where teams generate thousands of files monthly. The scenario tests capacity planning and budget forecasting skills.

Advanced Configuration Patterns

Enterprise policy (highest priority)
    ↓
~/.claude/settings.json (user global)
    ↓
.claude/settings.json (project - committed)
    ↓
.claude/settings.local.json (project - gitignored)
    ↓
Enterprise defaults (lowest priority)

json{
  "mcpServers": {
    "codebase-knowledge": {
      "command": "node",
      "args": ["./scripts/mcp-server.js"],
      "env": {
        "REPO_PATH": "./",
        "KNOWLEDGE_CACHE": "./.mcp-cache"
      }
    }
  }
}

Advanced candidates must understand configuration validation patterns, permission testing strategies, and rollback procedures for configuration changes that affect production systems.

Integration with Existing Development Workflows

Successful integration requires balancing developer autonomy with organizational governance. The exam tests your ability to design configurations that empower developers while maintaining security and quality standards.

Common Anti-Patterns and Failure Modes

The exam tests your ability to diagnose configuration problems from symptoms, design prevention strategies, and implement recovery procedures when anti-patterns are discovered in production systems.

Frequently Asked Questions

The code generation scenario appears in 4 of 6 randomized production scenarios and comprises 20% of Domain 3 (Claude Code Configuration & Workflows). Since Domain 3 represents 20% of the total exam weight, code generation topics can account for approximately 4% of the 60-question exam, or about 2-3 questions directly focused on code generation workflows.

CLAUDE.md files follow a strict loading hierarchy: user-level (~/.claude/CLAUDE.md) applies globally, project-level (./CLAUDE.md) is version-controlled and shared with teams, and directory-level files provide module-specific instructions. All files merge rather than override, enabling teams to establish shared standards while allowing individual customizations. Enterprise policies can override any user settings.

PreToolUse hooks run before tool execution and can validate, modify, or block operations using exit codes (exit code 2 blocks execution). PostToolUse hooks run after tool completion and typically handle formatting, linting, or quality checks. PreToolUse hooks receive tool inputs via environment variables, while PostToolUse hooks also receive tool outputs for processing.

Claude 4.6 Opus excels at complex architectural decisions, security reviews, and system design but costs significantly more per token. Claude 4.6 Sonnet provides balanced performance for feature development and bug fixes. Claude 4.5 Sonnet handles routine tasks like formatting and simple edits most economically. Production teams typically start with Sonnet variants and escalate to Opus for complex decisions.

Permission patterns use glob-style matching where "allow" permissions grant access and "deny" permissions (which take precedence) block dangerous operations. Typical CI/CD patterns allow specific build commands like "Bash(npm run build)", file operations in source directories like "Write(src/)", and block destructive operations like "Bash(rm -rf *)". Enterprise environments often implement additional policy layers.

Stop hooks run when Claude Code reaches end_turn and can continue the agent loop by returning non-empty output, which becomes a new user message. They're ideal for quality gates like "npm run typecheck" or "npm test" that must pass before work is considered complete. If the hook returns empty output, the agent stops normally.

Multi-pass review strategies segment large codebases by logical boundaries (modules, features, dependency graphs) while maintaining architectural coherence. Common passes include architectural review (overall structure), security review (authentication/authorization patterns), performance review (optimization opportunities), and integration review (API contracts and error handling). Each pass focuses on specific concerns while building on previous pass results.

MCP (Model Context Protocol) servers extend Claude Code with custom tools and data sources. In code generation scenarios, MCP servers can provide codebase knowledge, integrate with external APIs, access project-specific databases, or implement custom validation logic. They're configured in settings files and can be project-specific or globally available across all projects.

Production safety requires layered protection: restrictive permission patterns that block dangerous operations, PreToolUse hooks that validate all commands before execution, environment-specific configurations that limit production access, and enterprise policies that override local settings. Additionally, proper CI/CD integration ensures Claude Code works on feature branches with human review before production deployment.

Version control .claude/settings.json (shared team configuration), CLAUDE.md files (project instructions), and .claude/rules/ (team standards). Use .gitignore for .claude/settings.local.json (personal overrides), .mcp-cache/ (temporary files), and any files containing sensitive credentials or personal preferences. This pattern enables team consistency while preserving individual developer flexibility.