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situated-operations

Validate AI-generated operational plans with boundary-crossing verification and lifecycle simulation.

Updated Jul 26, 2026
Search Tags:#workflow#verification#governance#operations#risk-management#accountability
One-click install
npx skills add https://github.com/fagemx/wusanto --skill situated-operations
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: situated-operations
Source: https://github.com/fagemx/wusanto/tree/main/skills/situated-operations
Command: npx skills add https://github.com/fagemx/wusanto --skill situated-operations

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill addresses the accountability gap in AI-generated work by forcing explicit verification of operational boundaries, ensuring that AI-proposed workflows are safe, authorized, and ready for real-world execution.

Core Features & Use Cases

  • Operational Closure: Transforms vague AI proposals into concrete, nine-field closure records that define actors, interfaces, and fallback mechanisms.
  • Lifecycle Rehearsal: Provides a structured method to simulate the full service lifecycle, from contract to offboarding, without risking live accounts.
  • Use Case: Before deploying an AI-driven customer support agent, use this Skill to map out every boundary crossing, define provider-owned fallbacks for system failures, and verify that all authority limits are explicitly handled.

Quick Start

Use the situated-operations skill to review the current proposal and generate a closure record for all identified boundary breaks.

Frequently Asked Questions about situated-operations

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

FAQPage Schema
How do I verify AI-generated workflows before operational deployment?▼

Verifying AI-generated workflows requires enforcing strict boundary-crossing verification and lifecycle simulation. This skill validates operational plans by mapping boundary breaks and defining explicit provider-owned fallback mechanisms for accountability.

What is operational closure for AI agent deployment?▼

Operational closure transforms vague AI proposals into concrete nine-field records. These records explicitly define actors, interfaces, and fallback mechanisms, ensuring AI-driven service deployments are safe and authorized for real-world execution.

How do I simulate the full service lifecycle for AI customer support agents?▼

Simulating the service lifecycle involves rehearsing cross-boundary workflow reviews from contract to offboarding. This structured method maps authority limits and verifies failure recovery without risking live customer accounts.

Do I need to define fallback mechanisms for operational breaks in AI workflows?▼

Defining provider-owned fallbacks for every identified operational break is mandatory. This explicit definition ensures accountability and safe failure recovery across all boundary crossings within AI-proposed operational plans.

When do I need boundary-crossing verification for risk management?▼

Boundary-crossing verification is needed when deploying AI agents or reviewing cross-boundary workflows where accountability is critical. It ensures AI-proposed operations are safe, authorized, and ready for real-world execution.

What is the best way to enforce governance in AI-generated operational plans?▼

Enforcing governance in AI operational plans requires adhering to a strict operating solution template. This approach validates proposed workflows through rigorous operational gates and lifecycle simulation for accountability.

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