task-drill_skill

Overview

This skill guides users through decomposing tasks and deciding which parts humans should handle and which parts AI should handle. It supports four task types: Direct Problem Solving, Direct Output Generation, Collaborative Problem Solving, and Collaborative Output Generation. The skill produces step-by-step breakdowns, role assignment, and ready-to-use prompt templates. Use it whenever you need a structured plan to execute or delegate work between humans and AI.

How this skill works

When given a task, the skill first classifies it into one of the four types based on scope, information completeness, and interaction needs. It then assigns each subtask to either AI or a human, explains the rationale, and produces a clear sequence of steps. For every step it supplies the executor, explicit actions, human-to-AI prompt suggestions, and any human deliverables required. Prompts follow optimized templates for each task type to make handoffs actionable.

When to use it

• You need to decide which parts of a project an AI should perform and which require human judgment.
• You want a reproducible, stepwise plan for solving a problem or producing long-form output.
• A task seems complex or ambiguous and would benefit from multi-turn collaboration with AI.
• You need concrete prompt templates to hand AI clear instructions for each subtask.
• You’re preparing a workflow where responsibilities and dependencies must be explicit.

Best practices

• Classify the task first; that determines interaction style and granularity of steps.
• Prefer AI for data processing, pattern recognition, and first drafts; reserve humans for creativity, ethics, and final validation.
• Start collaborative work with a high-level framework, then iterate in defined rounds.
• Provide concise, context-rich inputs when calling AI to reduce clarification loops.
• Document dependencies between steps so later stages can rely on earlier outputs.

Example use cases

• Optimize a block of code: classify as Direct Problem Solving and provide a single-shot diagnosis plus suggested fixes.
• Write a technical report from data: use Direct Output Generation with a detailed brief and format requirements.
• Design system architecture: treat as Collaborative Problem Solving with iterative exploration and decision checkpoints.
• Create a product manual: use Collaborative Output Generation to establish structure, then refine sections across rounds.
• Plan a marketing campaign: decompose into research (AI), creative concepts (human+AI), and validation (human).