gpt-5-4-prompting

What problem does it solve?

Ambiguous or sprawling prompts to Codex/GPT-5.4 produce unreliable, unsupported, or overly verbose outputs that waste time and require repeated iterations. This skill provides a compact, block-structured prompting approach that forces clear task definitions, explicit output contracts, and verification rules so operator-style prompts yield predictable, actionable results.

Core Features & Use Cases

• XML block prompt recipe: Standardized tags for task, output contract, follow-through policy, verification, grounding, and safety to make prompts machine-parseable and stable.
• Verification and completeness contracts: Built-in patterns for verification_loop, completeness_contract, and missing_context_gating to avoid unsupported guesses during debugging, fixes, or reviews.
• Reusable templates and anti-patterns: Ready-to-use diagnosis, narrow-fix, root-cause review, research, and prompt-patching templates with examples and common antipatterns for reliable prompt construction.
• Use Cases: Diagnose failing tests, perform focused code reviews, implement small fixes safely, and craft research/recommendation prompts that require citations and grounding.

Quick Start

Use the gpt-5-4-prompting guidance to craft a compact XML-block prompt that asks Codex to diagnose a failing test and return root cause, evidence, and the smallest safe next step.