SAT, JULY 25, 2026
Independent · In‑Depth · Practitioner‑Tested
Claude Coding

Best Claude Opus 5 Prompts (2026) — Coding, Agents, and Complex Reasoning

Claude Opus 5 launched July 24, 2026 at $5/$25/M — the same price as Opus 4.8 with near-Fable-5 intelligence. The model has thinking ON by default and a five-level effort toggle (low/medium/high/max). At low effort it handles fast tasks efficiently; at max effort it works through hard problems with extended reasoning. These prompts are optimised specifically for Opus 5's new capabilities: the effort toggle, the automatic fallback, mid-conversation tool changes, and the 128K output window. Available via claude.ai Pro/Max, Claude Code, and the API as claude-opus-5.

⌨️ 6 prompts 🕐 Updated Jul 25, 2026
💡 How to use these prompts: Replace everything in [BRACKETS] with your specific details before sending. Click Copy to copy any prompt to your clipboard instantly.
1
Max Effort — Solve a Hard Problem
Use Opus 5 at max effort for your hardest problems
[SET EFFORT TO MAX BEFORE SENDING THIS PROMPT]

I have a problem that requires your deepest reasoning. Work through this step by step, explore multiple approaches, identify where you are uncertain, and arrive at the best answer you can.

Problem: [DESCRIBE YOUR HARD PROBLEM IN FULL DETAIL]

Context: [RELEVANT BACKGROUND — paste code, docs, data, or constraints]

I want you to:
1. Restate the problem in your own words to confirm understanding
2. Identify the 2-3 most promising approaches
3. Work through the best approach in full detail
4. State your conclusion with confidence level
5. Note what additional information would change your answer

Take as long as you need. This is a max-effort task.
2
Low Effort — Fast Classification or Routing
Use Opus 5 at low effort for high-volume classification tasks
[SET EFFORT TO LOW — this is a fast routing task, not a reasoning task]

Classify the following input into exactly one of these categories: [LIST YOUR CATEGORIES]

Rules:
- Return only the category name, nothing else
- If genuinely ambiguous, return the closest match
- Do not explain your reasoning

Input: [PASTE INPUT TO CLASSIFY]
3
Agentic Coding Task — Full Feature Implementation
Implement a complete feature autonomously using Claude Code or the API
[USE IN CLAUDE CODE OR API WITH TOOLS]

Implement the following feature in my codebase. Think through the architecture carefully before writing any code.

Feature: [DESCRIBE IN PLAIN ENGLISH WHAT IT SHOULD DO]

Repository context: [DESCRIBE YOUR STACK, KEY FILES, PATTERNS USED]

Requirements:
- [REQUIREMENT 1]
- [REQUIREMENT 2]
- [REQUIREMENT 3]

Definition of done: [HOW WE KNOW THE FEATURE IS COMPLETE]

Constraints:
- Do not modify [LIST FILES TO LEAVE ALONE]
- Match existing code style in [FILE EXAMPLE]
- All new functions must have docstrings

Work through this autonomously. After planning, implement, test, and summarise what you changed and why.
4
128K Output — Generate a Long Document
Generate a long complete document using Opus 5's 128K output window
Generate the following document in full. Do not truncate, summarise, or abbreviate any section. Use the full output window available to you.

Document type: [REPORT / SPEC / PLAYBOOK / CODEBASE / OTHER]
Length target: [APPROXIMATE WORD OR PAGE COUNT]
Audience: [WHO WILL READ THIS]

Structure:
[LIST EVERY SECTION WITH A ONE-LINE DESCRIPTION OF WHAT IT COVERS]

For each section:
- Write in full, not in outline form
- Use concrete examples, not generic statements
- Include all relevant detail a reader would need without coming back to ask

Source material to draw from: [PASTE REFERENCE MATERIAL]

Begin with Section 1 and continue until the document is complete.
5
Automatic Fallback Test — Check What Routes Through
Understand how Opus 5 automatic fallback affects your application
I am testing how Claude Opus 5's automatic fallback handles edge cases in my application. I want to understand which request types route to a fallback model vs which Opus 5 handles directly.

Please respond to the following requests in sequence and indicate after each one whether you handled it directly or whether it seems like a case where your fallback would normally trigger:

Request 1: [ROUTINE TASK]
Request 2: [MILDLY SENSITIVE TOPIC RELEVANT TO YOUR APP]
Request 3: [BORDERLINE CASE FOR YOUR USE CASE]
Request 4: [CLEARLY SENSITIVE CASE]

For each: answer the request if you can, then add one line: "Handled directly" or "This type would normally trigger fallback" with a brief reason.

This helps me calibrate my application's expectation of where fallback routing applies.
6
Multi-Turn Agent with Mid-Conversation Tool Changes
Use Opus 5 mid-conversation tool changes for research-then-action workflows
[USE WITH API — mid-conversation tool changes beta feature]

You are an autonomous research and action agent. I will give you a research objective. Work through it using the tools available to you. When the research is complete, I will update the tools available to you mid-conversation without invalidating the cache — at that point use the new tools to take action on what you found.

Research objective: [DESCRIBE WHAT YOU NEED TO FIND OUT]

Phase 1 — Research (use search and read tools):
1. Research the objective thoroughly
2. Produce a structured findings report
3. Identify the 3 most important actions to take based on findings
4. Signal you are ready for Phase 2 with: "RESEARCH COMPLETE — READY FOR ACTION TOOLS"

I will then add action tools (write, send, update) and you will proceed to Phase 2 without cache invalidation.