GPT-5.5 & GPT-5.5 Pro Master Prompts (June 2026)
Optimized prompts for OpenAI GPT-5.5 and GPT-5.5 Pro — native multimodality (text, vision, audio, speech), structured output, reasoning models, and function calling. Updated June 2026 for latest API capabilities.
📋 Prompt
/* GPT-5.5 MASTER PROMPT VERSION: 1.0.0 CAPABILITIES: Native Multimodality, Structured Output, Reasoning, Function Calling, Agents SDK */ **Model Configuration:** ┌─────────────────────────────────────────────┐ │ model: gpt-5.5 | gpt-5.5-pro | gpt-5.5-instant│ │ reasoning_effort: low | medium | high │ │ response_format: text | json_schema │ │ modalities: [text, vision, audio, speech] │ │ tools: [custom_functions, code_interpreter] │ └─────────────────────────────────────────────┘ **Prompt Architecture:** ┌─ SYSTEM ─────────────────────────────────────┐ │ Role: [EXPERTISE + CONSTRAINTS] │ │ Output: [FORMAT_SPEC] │ │ Rules: [SAFETY + QUALITY_BOUNDARIES] │ └──────────────────────────────────────────────┘ ┌─ CONTEXT ────────────────────────────────────┐ │ Background: [DOMAIN_KNOWLEDGE] │ │ Input Data: [TEXT | IMAGE | AUDIO | SPEECH] │ │ Constraints: [HARD_REQUIREMENTS] │ └──────────────────────────────────────────────┘ ┌─ INSTRUCTION ────────────────────────────────┐ │ 1. [STEP_ONE] — purpose + expected output │ │ 2. [STEP_TWO] — dependencies on step 1 │ │ 3. [STEP_N] — final integration │ └──────────────────────────────────────────────┘ **Reasoning Mode Selection:** - LOW: Simple classification, formatting, translation - MEDIUM: Code review, content writing, data analysis - HIGH: Architecture design, multi-step research, debugging complex systems **Multimodal Input Pattern:** ``` [IMAGE: screenshot of dashboard] Describe the metrics shown and identify anomalies. [AUDIO: customer_call.mp3] Extract action items and sentiment shifts. [TEXT: product spec] Given the above, generate a prioritized roadmap. ``` **Function Calling Pattern:** Define tools with clear JSON schemas. GPT-5.5 will chain calls intelligently. For agent workflows, use the Agents SDK pattern: plan → execute → verify → integrate. **Output Quality Gates:** - Structured outputs: validate against schema before returning - Code: include error handling and edge cases - Research: cite sources, flag uncertainty - Creative: provide 3+ variations with trade-off notes
💡 Tips
- Use reasoning_effort=high for any task requiring more than surface-level analysis
- Native multimodality means images/audio go directly in the prompt — no preprocessing needed
- Structured output with json_schema guarantees valid JSON — use for pipelines
- GPT-5.5 Pro has deeper reasoning and lower hallucination for critical applications
- Function calling chains are smarter in 5.5 — define tools once, let the model orchestrate
- For Agents SDK: start with a simple agent, add tools incrementally, test sandbox behavior
- GPT-5.5 on Amazon Bedrock (June 2026): use for enterprise deployments with AWS integration
GPT-5.5 & GPT-5.5 Pro — Complete Prompt Guide
OpenAI’s GPT-5.5 series represents a major leap in native multimodality, structured reasoning, and agentic capabilities. Available on the OpenAI API and Amazon Bedrock (as of June 2026).
Model Family
| Model | Best For | Key Feature |
|---|---|---|
| GPT-5.5 | General purpose, coding, writing | Balanced performance/cost |
| GPT-5.5 Pro | Research, architecture, critical apps | Deeper reasoning, lower hallucination |
| GPT-5.5 Instant | High-throughput, chat | Fastest, most affordable |
| GPT-5.5-Cyber | Enterprise security | Locked-down, private deployment |
What’s New vs GPT-5
- Native multimodality — images, audio, and speech are first-class inputs. No separate vision/audio models.
- Reasoning effort control — dial reasoning depth per request (
low/medium/high). - Structured output —
json_schemaresponse format guarantees valid JSON output. - Agents SDK — first-class agent orchestration with sandbox execution.
- Amazon Bedrock GA — enterprise deployment with AWS integration.
Prompting Best Practices
- Lead with output format. GPT-5.5 respects structure more than any previous OpenAI model — use it.
- Reasoning for complex tasks. Set
reasoning_effort=highfor multi-step problems. The model will “think” before answering. - Multimodal by default. Don’t describe images — include them. GPT-5.5 processes them natively.
- Function calling is production-grade. Define tools with JSON schemas and let the model chain them.
- Structured output for pipelines. Use
response_format: json_schemawhen the output feeds another system.
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