Instructor

The instructor skill, created by davila7 as part of the claude-code-templates suite, empowers AI agents to act as specialized supervisors. It enables agents to break down complex tasks into manageable steps and verify outputs before proceeding, ensuring higher accuracy in code generation and problem-solving workflows.

When to use it

• Complex Multi-Step Projects: When an AI agent needs to tackle large refactoring jobs or build multi-file applications that require sequential logic.
• High-Stakes Code Generation: For scenarios where output quality is critical, such as generating production-ready SQL queries or security-sensitive code.
• Iterative Debugging: When an agent encounters errors and needs a structured approach to isolate issues rather than guessing fixes immediately.
• Role-Based Interactions: To assign specific personas (e.g., "Senior Architect" or "QA Engineer") that dictate how the agent approaches a specific problem domain.

Key capabilities

• Task decomposition into logical sub-steps.
• Self-correction and verification loops before finalizing output.
• Context-aware persona adoption for specialized domains.
• Structured reasoning to guide the agent through complex logic flows.

Example prompts

• "Act as a senior backend engineer using the instructor skill to refactor this legacy Python module into an async architecture, verifying each step before moving on."
• "Use the instructor mode to debug this failing unit test suite; analyze the error logs first, propose a fix, and then validate the solution against the original requirements."
• "Instruct the agent to plan a database migration strategy for PostgreSQL, breaking down the schema changes into safe, reversible steps before executing any write operations."

Tips & gotchas

This skill is most effective when paired with clear initial context; vague instructions may lead to generic decomposition rather than targeted problem solving. Ensure the AI agent has access to relevant codebases or documentation, as the instructor relies on accurate information to validate its own reasoning steps effectively.