general-agentic

Require explicit predictions and verification before coding agent actions.

6|1|Updated Nov 26, 2025
One-click install
npx skills add https://github.com/CodingKaiser/kaiser-skills --skill general-agentic
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: general-agentic
Source: https://github.com/CodingKaiser/kaiser-skills/tree/main/general-agentic
Command: npx skills add https://github.com/CodingKaiser/kaiser-skills --skill general-agentic

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Defensive epistemology for coding agents reduces missteps by requiring explicit predictions, proactive error detection, and verification before every action.

Core Features & Use Cases

  • Explicit Prediction Protocol: forces the agent to forecast outcomes before tool use, enabling traceable reasoning.
  • Confusion Detection & Retreat: identifies surprises, logs assumptions, and halts to replan.
  • Context Window Discipline: maintains goal alignment over long tasks and prompts timely checkpointing.
  • Handoff & Collaboration: leaves a clean state for future agents with clear blockers and questions.

Quick Start

Use the general-agentic skill to begin a defensive reasoning loop: state your goal and constraints, and present explicit DOING/EXPECT/IF YES/IF NO steps before any action, then confirm with Q before executing a tool.

Frequently Asked Questions about general-agentic

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I prevent cascading errors when using a coding agent for multi-step tool use?

To prevent cascading errors in coding agents, enforce explicit predictions and verification before actions. This requires the agent to forecast outcomes and confirm expectations before executing steps that affect filesystems and builds.

What is defensive epistemology for coding agents?

Defensive epistemology for coding agents is a reasoning approach that reduces missteps by requiring explicit predictions, proactive error detection, and strict verification before every action is taken.

How do I maintain goal alignment over long coding tasks with a large context window?

Maintain goal alignment over long coding tasks by applying context window discipline, which prompts timely checkpointing, continuous log-keeping, and clear handoff steps to preserve state for future agents.

What is the best way to structure agent handoffs during multi-step automation tasks?

The best way to structure agent handoffs is by leaving a clean state with clear blockers and questions. This ensures future agents understand the current context and can resume automation tasks without confusion.

Does this defensive reasoning approach work for debugging and code generation?

Defensive reasoning works for debugging and code generation by applying an explicit prediction protocol. The agent states DOING/EXPECT/IF YES/IF NO steps before any action, enabling traceable reasoning and safer builds.

How do I stop an AI coding agent from making unexpected filesystem changes?

Stop an AI coding agent from making unexpected filesystem changes by using confusion detection and retreat. It identifies surprises, logs assumptions, and halts to replan before executing potentially destructive tool use.