openai-gpt5-prompting — community openai-gpt5-prompting, community, ide skills, Claude Code, Cursor, Windsurf

v1.0.0
GitHub

About this Skill

Perfect for Language Agents needing advanced prompt engineering capabilities with OpenAI GPT-5 jaunt, dont code.

ijindal1 ijindal1
[0]
[0]
Updated: 3/5/2026

Agent Capability Analysis

The openai-gpt5-prompting skill by ijindal1 is an open-source community AI agent skill for Claude Code and other IDE workflows, helping agents execute tasks with better context, repeatability, and domain-specific guidance.

Ideal Agent Persona

Perfect for Language Agents needing advanced prompt engineering capabilities with OpenAI GPT-5

Core Value

Empowers agents to generate unambiguous, testable, and robust prompts using system message templates, prioritizing safety bounds and formatting constraints, all while confirming current model names and features with $openai-docs

Capabilities Granted for openai-gpt5-prompting

Crafting prompts that balance speed and reliability for various tasks
Developing role-defined system messages for specific agent priorities
Optimizing prompt packs for edge case robustness and desired tradeoffs

! Prerequisites & Limits

  • Requires familiarity with OpenAI GPT-5 models and features
  • Needs access to $openai-docs for model information and updates
Labs Demo

Browser Sandbox Environment

⚡️ Ready to unleash?

Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

openai-gpt5-prompting

Install openai-gpt5-prompting, an AI agent skill for AI agent workflows and automation. Works with Claude Code, Cursor, and Windsurf with one-command setup.

SKILL.md
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GPT-5 Prompting (OpenAI)

Overview

Use this skill to produce prompts that are: unambiguous, testable, robust to edge cases, and aligned to the desired tradeoff between speed and reliability. Avoid hardcoding model IDs or limits; confirm current model names and features with $openai-docs when needed.

Prompt Pack (Use These Defaults)

System Message Template

Use a system message that defines role, priorities, safety bounds, and formatting constraints.

Required elements:

  • Role: what the model is (and is not) responsible for.
  • Output contract: exact format, sections, and any JSON schema constraints.
  • Non-goals: what to avoid (guessing, inventing APIs, ignoring inputs).
  • Clarification policy: what to ask if required info is missing.

Developer Message Template

Use a developer message for task-specific instructions, context, and constraints (without contradicting system).

Include:

  • Task statement (1 sentence).
  • Inputs provided and their meaning.
  • Constraints and preferences (libraries, time, cost).
  • Acceptance criteria (how you will judge success).

User Message Template

Make the user message concrete and data-heavy:

  • Provide examples (good and bad).
  • Provide edge cases.
  • Provide “definition of done”.

Workflow: Draft -> Test -> Patch

  1. Draft the prompt (system/developer/user separation).
  2. Add 3 to 10 targeted test cases:
  • Typical case, tricky case, adversarial case, empty/degenerate input.
  1. Run a “prompt diff” patch cycle:
  • Identify failure mode (ambiguity, missing constraints, competing goals).
  • Patch the smallest instruction that fixes it.
  • Re-run tests.

Structured Output Guidance

Prefer:

  • Explicit JSON schema (or a strict example) plus “no extra keys”.
  • Deterministic ordering only if needed.
  • “If you cannot comply, return an error object with fields …” (never silently fallback).

Common Failure Modes (And Fixes)

  1. Hallucinated facts:
  • Add: “If unknown, say I don’t know and ask for X.”
  • Add: cite-only-from-provided-sources rule when applicable.
  1. Format drift:
  • Add: strict schema, no prose, and a single top-level object.
  • Add: “Validate output against schema before responding.”
  1. Tool misuse:
  • Add: tool selection rule (“Only call tools when …”), plus examples.
  • Add: “Never fabricate tool outputs.”

References

See references/templates.md for copy-paste prompt templates and a test-case checklist.

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is openai-gpt5-prompting?

Perfect for Language Agents needing advanced prompt engineering capabilities with OpenAI GPT-5 jaunt, dont code.

How do I install openai-gpt5-prompting?

Run the command: npx killer-skills add ijindal1/jaunt. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for openai-gpt5-prompting?

Key use cases include: Crafting prompts that balance speed and reliability for various tasks, Developing role-defined system messages for specific agent priorities, Optimizing prompt packs for edge case robustness and desired tradeoffs.

Which IDEs are compatible with openai-gpt5-prompting?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for openai-gpt5-prompting?

Requires familiarity with OpenAI GPT-5 models and features. Needs access to $openai-docs for model information and updates.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add ijindal1/jaunt. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use openai-gpt5-prompting immediately in the current project.

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