shot

Inject a self-contained PUA prompt payload into sub-agents.

Updated Apr 3, 2026
One-click install
npx skills add https://github.com/handsomelong922/my-codex-skills --skill shot-handsomelong922
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: shot
Source: https://github.com/handsomelong922/my-codex-skills/tree/main/skills/shot
Command: npx skills add https://github.com/handsomelong922/my-codex-skills --skill shot-handsomelong922

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

PUA Shot is a self-contained, zero-dependency prompt payload designed to inject a complete instruction set into a target sub-agent, enabling the strongest PUA effects without requiring external references.

Core Features & Use Cases

  • Self-contained payload with zero dependencies and no external references.
  • Instant context injection for sub-agent tasks, enabling rapid, decisive action.
  • Triggerable via multiple phrases: '/pua:shot', '/pua shot', 'PUA浓缩', 'shot mode', '最强PUA', '全量注入'.
  • Suitable for injecting into sub-agents via Read tool to ensure context is embedded and immediately actionable.

Quick Start

Inject the shot payload into the target sub-agent to activate the complete instruction set in one go.

Frequently Asked Questions about shot

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

FAQPage Schema
What is PUA prompt injection for AI sub-agents?

Self-contained prompt injection works by deploying a zero-dependency payload that injects a complete instruction set into a target sub-agent. This ensures the strongest PUA effects without requiring external references.

How do I inject a prompt payload into a sub-agent workflow?

You inject the shot payload into a target sub-agent via the Read tool to ensure context is embedded and immediately actionable. Trigger it using phrases like '/pua:shot' or 'PUA浓缩' to activate the complete instruction set instantly.

Can I orchestrate multi-layer agent frameworks without external dependencies?

Yes, this self-contained approach supports zero-dependency orchestration across a four-layer agent framework (P10→P9→P8→P7). It enforces robust owner delegation, end-to-end validation, and safety gating without needing external references.

Does self-contained prompt injection work for complex task validation?

Yes, self-contained prompt injection supports complex task validation by enforcing end-to-end validation and safety gating through explicit protocol documents. It coordinates high-intensity instructions across a four-layer agent framework for robust owner delegation.

When should I use zero-dependency prompt payloads in AI agent workflows?

Use zero-dependency prompt payloads when you need to inject complete instruction sets into sub-agents rapidly without relying on external references. They are suitable for complex tasks requiring high-intensity PUA effects and immediate actionable context.