operators-edge

Orchestrate state, proof, and gates during coding tasks.

Updated Jan 4, 2026
One-click install
npx skills add https://github.com/DazedtilDawn/operators-edge --skill operators-edge
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: operators-edge
Source: https://github.com/DazedtilDawn/operators-edge/tree/main/.claude/skills/operators-edge
Command: npx skills add https://github.com/DazedtilDawn/operators-edge --skill operators-edge

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Runs the Operator's Edge loop to orchestrate state, proofs, gates, and adaptation checks for coding tasks, debugging, refactor, and system changes, reducing manual overhead and preventing undetected drift.

Core Features & Use Cases

  • State management with pre- and post-action updates (active_context.yaml, mismatches, lessons)
  • The 6-Check Adaptation Loop ensuring mismatch handling, plan revision, tool switching, memory updates, and proof generation
  • Proof-by-default capturing outputs, diffs, tests, and archives
  • Gates enforcement via hard, soft, and confirmation gates
  • Memory system for learning and recalling lessons
  • Three Gears rounds ACTIVE, PATROL, and DREAM to manage objectives and surface findings

Quick Start

Activate the Operator's Edge loop to begin a coding task from planning through verification.

Frequently Asked Questions about operators-edge

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

FAQPage Schema
How do I manage state and prevent drift during automated debugging and refactoring?

Automated coding tasks can capture proof by default by recording outputs, diffs, and tests. This ensures every action generates verifiable evidence, preventing silent failures and undetected drift during system changes.

What is the best way to enforce validation gates for complex coding tasks?

Coding tasks use a six-check adaptation loop to handle mismatches, revise plans, switch tools, update memory, and generate proof. This iterative process ensures continuous alignment and adaptive response throughout system changes.

Can I automate proof capture for outputs and diffs when changing code?

Debugging and refactoring tasks maintain context using a memory system that learns and recalls lessons. It operates across three gears—ACTIVE, PATROL, and DREAM—to manage objectives and surface findings during system changes.

How does an adaptation loop work for handling mismatches in coding tasks?

State management during debugging and refactoring is handled through pre- and post-action updates using active_context.yaml. This tracks mismatches and lessons, reducing manual overhead and preventing undetected drift across system changes.

Do I need a memory system to track lessons during software debugging?

Coding tasks enforce validation using hard, soft, and confirmation gates. This gated action approach ensures system changes meet specific criteria before proceeding, reducing manual oversight and preventing errors during refactoring.