openai-gpt5-prompting — community openai-gpt5-prompting, community, ide skills

v1.0.0
GitHub

About this Skill

Perfect for Advanced AI Agents needing robust and testable prompt generation for OpenAI GPT-5 models. Write, critique, and iterate prompts for OpenAI GPT-5 series models. Use for tasks like: (1) turning vague requirements into high-signal instructions, (2) selecting between quick vs deep reasoning beh

ijindal1 ijindal1
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Updated: 3/12/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 7/11

This page remains useful for operators, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution Locale and body language aligned
Review Score
7/11
Quality Score
35
Canonical Locale
en
Detected Body Locale
en

Perfect for Advanced AI Agents needing robust and testable prompt generation for OpenAI GPT-5 models. Write, critique, and iterate prompts for OpenAI GPT-5 series models. Use for tasks like: (1) turning vague requirements into high-signal instructions, (2) selecting between quick vs deep reasoning beh

Core Value

Empowers agents to create unambiguous and reliable prompts using a system message template that defines role, priorities, safety bounds, and formatting constraints, ensuring alignment with the desired tradeoff between speed and reliability via OpenAI's API and $openai-docs.

Ideal Agent Persona

Perfect for Advanced AI Agents needing robust and testable prompt generation for OpenAI GPT-5 models.

↓ Capabilities Granted for openai-gpt5-prompting

Generating testable prompts for edge cases
Defining role and priorities for AI tasks
Ensuring safety bounds for sensitive information

! Prerequisites & Limits

  • Requires knowledge of OpenAI GPT-5 models and features
  • Must confirm current model names and features with $openai-docs

Why this page is reference-only

  • - The underlying skill quality score is below the review floor.

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

After The Review

Decide The Next Action Before You Keep Reading Repository Material

Killer-Skills should not stop at opening repository instructions. It should help you decide whether to install this skill, when to cross-check against trusted collections, and when to move into workflow rollout.

Install Path

Start With Installation And Validation

If this skill is worth continuing with, the next step is to confirm the install command, CLI write path, and environment validation.
Trusted Recheck

Cross-Check Against Trusted Picks

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Workflow

Move To Workflow Collections For Team Rollout

When the goal shifts from a single skill to team handoff, approvals, and repeatable execution, move into workflow collections.
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

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 Advanced AI Agents needing robust and testable prompt generation for OpenAI GPT-5 models. Write, critique, and iterate prompts for OpenAI GPT-5 series models. Use for tasks like: (1) turning vague requirements into high-signal instructions, (2) selecting between quick vs deep reasoning beh

How do I install openai-gpt5-prompting?

Run the command: npx killer-skills add ijindal1/jaunt/openai-gpt5-prompting. 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: Generating testable prompts for edge cases, Defining role and priorities for AI tasks, Ensuring safety bounds for sensitive information.

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 knowledge of OpenAI GPT-5 models and features. Must confirm current model names and features with $openai-docs.

↓ 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/openai-gpt5-prompting. 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.

! Reference-Only Mode

This page remains useful for installation and reference, but Killer-Skills no longer treats it as a primary indexable landing page. Read the review above before relying on the upstream repository instructions.

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

openai-gpt5-prompting

Install openai-gpt5-prompting, an AI agent skill for AI agent workflows and automation. Review the use cases, limitations, and setup path before rollout.

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

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.

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