Claude Opus 5.5 Prompts: 50+ Powerful AI Prompts for Coding, Research, Writing, Business and Advanced Workflows in 2026
Claude Opus 5.5 Prompts: 50+ Powerful AI Prompts for Coding, Research, Writing, Business and Advanced Workflows in 2026
Claude Opus 5.5 is one of the biggest AI model releases of September 2026, and it is quickly becoming a major tool for developers, researchers, writers, businesses, and advanced AI users.
Anthropic introduced Claude Opus 5.5 on September 22, 2026, as the first model in its Claude 5.5 family. Anthropic says the model performs at the level of Claude Fable 5.1 on most work while costing 40% less to run than Opus 5. The company also highlights improvements for complex professional work, coding, long-running tasks, and advanced AI workflows.
What makes the release particularly interesting for prompt engineers is that Anthropic has also published specific guidance for prompting Opus 5.5. Its documentation discusses effort calibration, long-running tasks, progress updates, multi-agent workflows, complex visual inputs, multi-app workflows, and other prompting patterns.
This guide contains 50+ Claude Opus 5.5 prompts that you can copy, customize, and use for real-world work.
What Is Claude Opus 5.5?
Claude Opus 5.5 is Anthropic's newest Opus-series model released in September 2026.
It is designed for demanding tasks where users need more than a short conversational answer.
Examples include:
Software development
Code review
Debugging
Research
Business analysis
Document analysis
Technical writing
Content creation
Data interpretation
Strategic planning
Long-running projects
Complex reasoning
Professional knowledge work
AI-assisted workflows
Anthropic says Opus 5.5 is a major performance step over Opus 5 and reports that early testers saw substantial improvements on difficult tasks. One example published by Anthropic involved a large code migration involving hundreds of thousands of lines of code.
For users, however, the biggest lesson is simple:
A more capable model does not automatically mean better results from a vague prompt.
The quality of your instructions still matters.
Why Claude Opus 5.5 Is Trending in 2026
The AI market has become increasingly focused on models that can complete larger tasks rather than simply answer individual questions.
Instead of asking:
"Write some Python code."
Users increasingly want AI to:
Understand an existing project.
Identify the problem.
Plan the work.
Make changes.
Test the result.
Find errors.
Improve the implementation.
Explain what changed.
Stop when the requested definition of done has been reached.
Anthropic's own guidance for Opus 5.5 emphasizes telling the model what "done" looks like, then allowing it to work through the task. The guidance also notes that Opus 5.5 already thinks before responding, meaning prompts do not necessarily need repetitive instructions such as "think carefully."
This represents an important change in prompt engineering.
The best prompt is increasingly becoming less like:
"Give me an answer."
And more like:
"Here is the objective, context, constraints, success criteria, available resources, and definition of done. Complete the task and verify the result."
Claude Opus 5.5 Prompt Formula
A powerful Opus 5.5 prompt can use this structure:
ROLE:
You are an expert in [domain].
OBJECTIVE:
Complete [specific task].
CONTEXT:
Here is the relevant background:
[context]
INPUT:
[documents, code, data, requirements, etc.]
CONSTRAINTS:
- [constraint 1]
- [constraint 2]
- [constraint 3]
PROCESS:
Work through the task systematically.
Inspect the available information before making assumptions.
Ask for clarification only when an ambiguity blocks progress.
QUALITY REQUIREMENTS:
- [quality requirement]
- [quality requirement]
- [quality requirement]
DEFINITION OF DONE:
The task is complete when:
- [condition 1]
- [condition 2]
- [condition 3]
FINAL OUTPUT:
Provide:
1. [output]
2. [output]
3. [output]
This structure works particularly well for complex tasks because it gives the model a target rather than simply requesting an isolated response.
10 Rules for Better Claude Opus 5.5 Prompts
1. Define the outcome
Don't only describe what you want the AI to do.
Explain what the finished result should look like.
Bad:
Improve my website.
Better:
Audit my website's homepage and produce a prioritized improvement plan covering UX, accessibility, SEO, performance, conversion, and mobile usability.
Define the expected result for each recommendation and separate critical issues from optional improvements.
2. Give Claude relevant context
Complex models can work with substantial context, but irrelevant information can still make tasks less efficient.
Provide the information that actually affects the decision.
3. Define constraints
Tell Claude what it must not do.
For example:
Do not rewrite the existing API.
Do not introduce new dependencies unless necessary.
Preserve the current database schema.
Maintain backward compatibility.
4. Define success criteria
Instead of saying:
Make the code better.
Say:
The final implementation should:
- pass all existing tests
- introduce no breaking API changes
- handle invalid input safely
- maintain current behavior
- improve readability
- include tests for the newly fixed edge cases
5. Tell it when the task is complete
This is particularly useful for long-running workflows.
Continue until all requested changes have been implemented and verified.
Stop when:
- all requirements are satisfied
- tests have been executed
- remaining issues are documented
- no additional changes are required for the requested scope
6. Separate facts from assumptions
Use:
Clearly distinguish:
1. Facts directly supported by the supplied information.
2. Reasonable inferences.
3. Assumptions that require verification.
7. Ask for verification
Don't simply ask for an answer.
Ask the model to check the result.
After completing the task, review your output against every requirement and identify anything that remains incomplete.
8. Don't unnecessarily tell Opus 5.5 to "think harder"
Anthropic's Opus 5.5 prompting documentation specifically notes that the model already thinks before responding. Its guidance focuses instead on calibrating effort appropriately for the task.
So rather than repeatedly writing:
Think very carefully.
Think deeply.
Think step by step.
Think harder.
Use explicit objectives and quality criteria.
9. Give the model a stopping condition
For example:
Do not continue expanding the scope after the requested requirements have been satisfied.
This can help keep large tasks focused.
10. Ask for a useful final report
For complex tasks, request:
At the end, provide:
- what was completed
- what changed
- what was verified
- any unresolved issues
- recommended next steps
50+ Claude Opus 5.5 Prompts
Now let's get to the practical section.
These prompts are designed to be copied and customized.
Claude Opus 5.5 Coding Prompts
Prompt 1: Build a Complete Feature
Act as a senior software engineer.
I need to add the following feature:
[DESCRIBE FEATURE]
First inspect the existing architecture, relevant files, dependencies, interfaces, and tests.
Then create an implementation plan.
Implement the feature while preserving existing behavior.
Requirements:
- follow the existing coding conventions
- minimize unnecessary changes
- handle errors and edge cases
- add or update tests
- avoid introducing unnecessary dependencies
Definition of done:
- the feature works as requested
- existing functionality remains intact
- relevant tests pass
- edge cases are covered
- the final implementation is documented
At the end, summarize what changed and what was verified.
Prompt 2: Debug a Difficult Bug
Act as an expert debugging engineer.
Here is the problem:
[BUG DESCRIPTION]
Here is the relevant code:
[CODE]
Analyze the problem systematically.
Identify:
1. The most likely root cause.
2. Evidence supporting the diagnosis.
3. Alternative possible causes.
4. The smallest safe fix.
5. Tests that should be added to prevent regression.
Then implement the fix if the environment allows it.
Do not change unrelated functionality.
Afterward, verify the solution against the original failure and relevant edge cases.
Prompt 3: Refactor Existing Code
Review the following code as a senior software architect:
[CODE]
Identify:
- unnecessary complexity
- duplicated logic
- maintainability problems
- potential bugs
- performance issues
- unclear abstractions
- poor naming
- missing tests
Then propose a refactoring strategy.
Implement only changes that provide meaningful improvement.
Preserve the existing external behavior unless a breaking change is explicitly required.
Explain the important changes and verification performed.
Prompt 4: Code Review
Perform a rigorous code review of this pull request:
[CODE OR DIFF]
Review it for:
- correctness
- security
- performance
- maintainability
- reliability
- error handling
- edge cases
- test coverage
- API compatibility
Classify findings as:
CRITICAL
HIGH
MEDIUM
LOW
For every finding provide:
- location
- problem
- why it matters
- recommended fix
Do not report stylistic preferences unless they materially affect maintainability.
Prompt 5: Generate Tests
Analyze this implementation:
[CODE]
Create a comprehensive testing strategy.
Include:
- happy paths
- edge cases
- invalid inputs
- failure scenarios
- boundary conditions
- regression tests
- security-related cases where relevant
Then generate the tests using the project's existing testing framework.
Avoid testing implementation details that unnecessarily couple the tests to the current code structure.
Prompt 6: Optimize Slow Code
Act as a performance engineer.
Analyze this code:
[CODE]
Identify the likely performance bottlenecks.
For each bottleneck explain:
- current behavior
- likely cost
- expected impact
- proposed optimization
- tradeoffs
Then implement the safest high-impact optimizations.
Do not optimize purely for theoretical performance if it significantly harms readability or reliability.
Provide a before/after explanation and verification strategy.
Prompt 7: Build an API
Design and implement an API for:
[PROJECT DESCRIPTION]
Requirements:
- authentication
- validation
- structured errors
- pagination where appropriate
- rate limiting considerations
- logging
- security
- versioning
- documentation
- automated tests
First inspect the existing project architecture.
Then create the API design and implementation plan before modifying files.
Definition of done:
- endpoints work
- validation works
- errors are predictable
- tests cover important cases
- documentation explains usage
Prompt 8: Legacy Code Migration
I need to migrate this legacy codebase:
[DESCRIPTION]
Target:
[TARGET TECHNOLOGY]
Analyze the current architecture and identify compatibility risks.
Create a phased migration plan that minimizes downtime and regression risk.
For each phase specify:
- objective
- files/components affected
- dependencies
- testing requirements
- rollback strategy
Do not migrate everything blindly.
Prioritize the safest incremental path.
Prompt 9: Security Audit
Act as a defensive application security reviewer.
Audit the following code:
[CODE]
Look for:
- authentication weaknesses
- authorization problems
- injection risks
- insecure data handling
- secrets exposure
- unsafe file handling
- session issues
- dependency risks
- sensitive information leakage
For every finding provide:
severity
location
explanation
safe remediation
Do not provide instructions for exploiting real systems.
Focus on defensive remediation and verification.
Prompt 10: Build a Project From Requirements
Act as a senior full-stack engineer.
Build the following application:
[APP DESCRIPTION]
Requirements:
[REQUIREMENTS]
Before implementation:
1. Analyze the requirements.
2. Identify ambiguities.
3. Design the architecture.
4. Define the major components.
5. Define testing requirements.
Then implement the project.
Keep the architecture simple unless complexity is justified.
Definition of done:
- core functionality works
- UI is usable
- errors are handled
- important edge cases are covered
- tests exist
- setup instructions are provided
Claude Opus 5.5 Research Prompts
Prompt 11: Deep Research
Act as a professional research analyst.
Research this topic:
[TOPIC]
Objectives:
[OBJECTIVES]
Create a structured analysis covering:
- background
- current state
- important developments
- competing viewpoints
- evidence
- uncertainties
- practical implications
Separate verified facts from interpretation.
When information is uncertain, clearly label it.
End with:
1. Key findings
2. Evidence gaps
3. Important questions
4. Practical conclusions
Prompt 12: Research a New AI Tool
Research the AI tool:
[TOOL NAME]
Analyze:
- what it does
- target users
- major features
- strengths
- limitations
- pricing information if publicly available
- integrations
- privacy considerations
- major use cases
- competing tools
- current developments
Prioritize recent and primary sources.
Clearly separate official claims from independent reporting.
Finish with a concise buyer/user guide.
Prompt 13: Compare AI Models
Compare these AI models:
[MODEL A]
[MODEL B]
[MODEL C]
Evaluate them across:
- coding
- reasoning
- writing
- research
- long-context work
- multimodal capabilities
- speed
- cost
- tool use
- workflow automation
Do not invent benchmark results.
Use only verifiable information.
Present factual differences first, then explain which type of user each model may be suited to based on those documented differences.
Prompt 14: Research a Business Opportunity
Analyze this potential business:
[BUSINESS IDEA]
Research the market and evaluate:
- target customers
- customer pain points
- competitors
- existing solutions
- potential differentiation
- pricing models
- distribution channels
- operational requirements
- risks
- possible AI advantages
Separate verified market information from hypotheses.
End with a list of experiments that could validate the idea before significant investment.
Prompt 15: Summarize a Long Report
Analyze the following report:
[DOCUMENT]
Create:
1. Executive summary
2. Main findings
3. Important statistics
4. Key arguments
5. Evidence
6. Risks
7. Contradictions
8. Unresolved questions
9. Practical implications
Do not omit important caveats.
Clearly distinguish what the document states from your own analysis.
Claude Opus 5.5 Writing Prompts
Prompt 16: Write a High-Quality Blog Post
Act as an expert SEO content writer.
Write a comprehensive article about:
[TOPIC]
Target audience:
[AUDIENCE]
Search intent:
[SEARCH INTENT]
Requirements:
- useful original explanations
- clear headings
- practical examples
- actionable advice
- natural keyword usage
- concise paragraphs
- strong introduction
- FAQ section
- conclusion
Avoid keyword stuffing and generic filler.
The article should help a reader solve a real problem rather than merely summarize the topic.
Prompt 17: Improve an Existing Article
Audit this article:
[ARTICLE]
Improve it for:
- clarity
- usefulness
- structure
- originality
- readability
- search intent
- examples
- factual precision
Do not rewrite merely for the sake of changing wording.
Preserve valuable information.
Identify weak sections before rewriting them.
Then provide the improved version.
Prompt 18: Write a Technical Tutorial
Write a beginner-friendly but technically accurate tutorial about:
[TOPIC]
Structure it as:
1. What it is
2. Why it matters
3. Requirements
4. Step-by-step setup
5. Example
6. Common mistakes
7. Troubleshooting
8. Advanced tips
9. FAQ
10. Final checklist
Assume the reader has limited prior knowledge.
Do not skip important technical steps.
Prompt 19: Rewrite for Human-Like Style
Rewrite the following content:
[CONTENT]
Make it:
- natural
- clear
- conversational
- specific
- useful
- confident without exaggeration
Remove:
- repetitive phrases
- generic filler
- unnecessary headings
- awkward transitions
- robotic wording
Preserve the factual meaning.
Do not invent information.
Prompt 20: Create Multiple Headlines
Generate 30 headline ideas for:
[TOPIC]
Create a mixture of:
- SEO headlines
- curiosity headlines
- how-to headlines
- list headlines
- beginner headlines
- advanced headlines
- news-style headlines
Avoid misleading clickbait.
Make every headline communicate a clear benefit or topic.
Claude Opus 5.5 Business Prompts
Prompt 21: Business Strategy
Act as a business strategy consultant.
Analyze:
[BUSINESS]
Current situation:
[DETAILS]
Goal:
[GOAL]
Create a strategy covering:
- current challenges
- opportunities
- customer segments
- competitive environment
- operational priorities
- revenue opportunities
- risks
- implementation roadmap
Separate assumptions from evidence.
Prioritize practical actions that can be tested.
Prompt 22: Customer Research
Analyze these customer interviews:
[INTERVIEWS]
Identify:
- recurring pain points
- desired outcomes
- objections
- buying motivations
- unmet needs
- language customers repeatedly use
- differences between customer segments
Do not treat one person's opinion as a universal trend.
Create a prioritized list of insights supported by multiple pieces of evidence.
Prompt 23: Create a Marketing Strategy
Build a marketing strategy for:
[PRODUCT]
Target audience:
[AUDIENCE]
Budget:
[BUDGET]
Primary goal:
[GOAL]
Develop:
- positioning
- messaging
- content strategy
- acquisition channels
- conversion strategy
- retention strategy
- measurement framework
For each recommendation explain the reasoning and assumptions.
Prompt 24: Create a Sales System
Design a sales workflow for:
[BUSINESS]
Target customer:
[CUSTOMER]
Product:
[PRODUCT]
Create:
1. Lead qualification criteria
2. Discovery questions
3. Sales messaging
4. Follow-up sequence
5. Objection handling
6. CRM stages
7. Metrics
8. Automation opportunities
Keep the workflow practical for a small team.
Prompt 25: Analyze a Competitor
Analyze this competitor:
[COMPETITOR]
Evaluate:
- target audience
- product positioning
- features
- pricing
- marketing approach
- customer experience
- strengths
- limitations
- differentiation opportunities
Clearly separate observable facts from interpretation.
Do not invent information that cannot be verified.
Claude Opus 5.5 SEO Prompts
Prompt 26: Keyword Cluster
Create a topical SEO map for:
[MAIN TOPIC]
Generate clusters for:
- primary topics
- supporting topics
- beginner questions
- advanced questions
- comparison searches
- problem-solving searches
- commercial intent
- informational intent
Avoid keyword stuffing.
Group keywords by search intent rather than simply generating a giant list.
Prompt 27: Content Cluster
Create a 30-article content cluster around:
[TOPIC]
For each article provide:
- title
- search intent
- primary keyword
- secondary topics
- reader problem
- unique angle
- internal linking opportunities
Avoid creating articles that target essentially the same search intent.
Prompt 28: SEO Content Audit
Audit this page:
[CONTENT]
Check:
- search intent
- topical coverage
- structure
- headings
- internal linking opportunities
- missing questions
- duplication
- readability
- factual claims
- FAQ opportunities
Give recommendations based on usefulness and topical completeness rather than keyword density alone.
Prompt 29: Featured Snippet Content
Analyze the topic:
[TOPIC]
Identify questions that could be answered clearly in short formats.
Create concise answers for:
- definition questions
- how-to questions
- comparison questions
- list questions
- troubleshooting questions
Then explain where longer explanations are necessary.
Prioritize usefulness over artificially shortening answers.
Prompt 30: AI Search Optimization
Analyze this article for visibility in modern AI-powered search systems:
[ARTICLE]
Improve it by adding:
- clear definitions
- direct answers
- useful entities and concepts
- structured explanations
- factual context
- comparisons
- examples
- FAQs
- concise answer blocks
Do not manipulate or stuff keywords.
Make the article genuinely easier for both humans and search systems to understand.
Claude Opus 5.5 Document Analysis Prompts
Prompt 31: Contract Analysis
Analyze this contract:
[CONTRACT]
Identify:
- major obligations
- deadlines
- payment terms
- termination conditions
- renewal conditions
- unusual clauses
- potential ambiguities
- important questions to ask a qualified professional
Quote only short relevant excerpts when necessary.
Do not present this as legal advice.
Prompt 32: Resume Analysis
Analyze this resume:
[RESUME]
Evaluate it for:
- clarity
- relevance
- measurable achievements
- structure
- skills presentation
- role alignment
- unnecessary content
Target role:
[ROLE]
Then create an improved version while preserving truthful information.
Do not invent qualifications or achievements.
Prompt 33: Meeting Analysis
Analyze this meeting transcript:
[TRANSCRIPT]
Extract:
- decisions
- action items
- owners
- deadlines
- unresolved questions
- risks
- important context
Then produce a concise meeting summary.
Do not assign an owner or deadline when the transcript does not support one.
Prompt 34: PDF Research Assistant
Analyze the supplied document carefully.
Answer these questions:
[QUESTIONS]
For each answer:
- identify the relevant section
- summarize the evidence
- distinguish explicit statements from inference
- mention important limitations
If the document does not contain enough information, say so rather than guessing.
Claude Opus 5.5 Data Analysis Prompts
Prompt 35: Analyze a Dataset
Analyze this dataset:
[DATA]
First inspect the structure and identify:
- columns
- data types
- missing values
- duplicates
- anomalies
- potential data quality problems
Then analyze:
- major patterns
- trends
- relationships
- outliers
- important segments
Do not claim causation from correlation.
Clearly explain limitations.
Prompt 36: Create a Business Dashboard Plan
Design a dashboard for:
[BUSINESS]
Business objectives:
[OBJECTIVES]
Recommend:
- KPIs
- supporting metrics
- filters
- charts
- alerts
- reporting frequency
For every metric explain why it matters and what decision it should support.
Avoid vanity metrics that do not influence decisions.
Prompt 37: Explain Data to Executives
Turn this analysis into an executive briefing:
[DATA/ANALYSIS]
The audience is non-technical.
Explain:
- what happened
- why it matters
- what changed
- important risks
- recommended questions
- possible actions
Do not oversimplify important uncertainty.
Claude Opus 5.5 Creative Prompts
Prompt 38: Generate Content Ideas
Generate 50 original content ideas for:
[NICHE]
Target audience:
[AUDIENCE]
Prioritize ideas that:
- solve specific problems
- have practical value
- can become standalone articles/videos/posts
- address current user questions
- avoid repetitive concepts
Group the ideas into clear categories.
Prompt 39: YouTube Video Script
Write a YouTube script about:
[TOPIC]
Audience:
[AUDIENCE]
Target duration:
[DURATION]
Structure:
1. Hook
2. Problem
3. Explanation
4. Examples
5. Practical demonstration
6. Key takeaways
7. CTA
Avoid exaggerated claims.
Make the script sound natural when spoken aloud.
Prompt 40: Social Media Content System
Create a 30-day social content plan for:
[BRAND/NICHE]
Platforms:
[PLATFORMS]
For each day provide:
- topic
- hook
- format
- key message
- CTA
Create different content pillars instead of repeating the same idea.
Prioritize educational, entertaining, and useful content.
Prompt 41: Newsletter
Write a newsletter about:
[TOPIC]
Audience:
[AUDIENCE]
Tone:
[TONE]
Include:
- strong opening
- useful insight
- practical examples
- one memorable takeaway
- clear CTA
Avoid generic introductions and unnecessary filler.
Advanced Claude Opus 5.5 Workflow Prompts
The most interesting use of advanced models is not always individual prompts.
It is workflow design.
Prompt 42: AI Project Manager
Act as my AI project manager.
Project:
[PROJECT]
Goal:
[GOAL]
Deadline:
[DEADLINE]
Resources:
[RESOURCES]
Break the project into logical phases.
For each phase define:
- objective
- tasks
- dependencies
- risks
- completion criteria
Track the project's state as we continue.
When information is missing, identify the missing dependency rather than silently inventing it.
Keep the project focused on the original objective.
Prompt 43: Research-to-Article Workflow
Act as a research-to-publishing assistant.
Topic:
[TOPIC]
Complete this workflow:
1. Define the search intent.
2. Identify important subtopics.
3. Research the topic.
4. Separate facts from interpretations.
5. Create an article structure.
6. Draft the article.
7. Audit the draft for missing information.
8. Improve clarity and usefulness.
9. Create an FAQ.
10. Create SEO metadata.
Do not invent sources, statistics, quotations, or claims.
The final article should be useful independently of the workflow.
Prompt 44: Product Development Workflow
Act as a product development assistant.
Product:
[PRODUCT]
Goal:
[GOAL]
Work through:
Research → Requirements → User stories → Architecture → Implementation plan → Testing → Launch checklist.
At every stage:
- summarize the current state
- identify blockers
- preserve important decisions
- avoid unnecessary scope expansion
Definition of done:
[DEFINITION]
Prompt 45: Personal Knowledge Assistant
Act as a knowledge-management assistant.
I will provide notes, documents, ideas, and tasks.
Your job is to:
- organize information
- identify connections
- summarize important decisions
- detect contradictions
- identify missing information
- convert ideas into actionable tasks
- maintain consistent terminology
Never invent information that is not present in my material.
When uncertain, explicitly label the uncertainty.
Prompt 46: Multi-Agent Research Workflow
Design a multi-agent research workflow for:
[TASK]
Create specialized roles for:
1. Research
2. Evidence verification
3. Analysis
4. Counterargument review
5. Final synthesis
Define:
- input for each role
- output for each role
- handoff format
- verification process
- final quality criteria
Minimize duplicated work.
The final agent should synthesize evidence rather than blindly combining every output.
Prompt 47: Long-Running Coding Task
You are responsible for completing this engineering task:
[TASK]
Before starting, inspect the repository and identify the relevant architecture.
Work systematically through the task.
Requirements:
- maintain existing behavior
- avoid unrelated refactoring
- test important changes
- verify integration points
- document significant decisions
If you encounter a blocker, explain precisely what is blocking progress.
Continue until the definition of done is satisfied.
Definition of done:
[CRITERIA]
Anthropic's own guidance for Opus 5.5 specifically discusses how to steer long runs and recommends defining what "done" means before letting the model work.
Prompt 48: Self-Review Workflow
Complete the requested task:
[TASK]
After producing the initial result, perform a separate quality review.
Check for:
- factual errors
- missing requirements
- contradictions
- weak reasoning
- unsupported assumptions
- formatting problems
- edge cases
- unnecessary content
Then revise the result where necessary.
Return:
1. Final result
2. Important corrections made
3. Remaining limitations
Prompt 49: Decision Analysis
Help me analyze this decision:
[DECISION]
Options:
[OPTIONS]
Criteria:
[CRITERIA]
For each option analyze:
- advantages
- disadvantages
- costs
- risks
- dependencies
- short-term consequences
- long-term consequences
- reversibility
Do not choose for me.
Identify the information that would most reduce uncertainty before making the decision.
Prompt 50: Expert Advisor
Act as an expert advisor in:
[DOMAIN]
My objective:
[OBJECTIVE]
Before recommending an approach:
1. Identify the important facts.
2. Identify missing information.
3. Identify constraints.
4. Identify potential risks.
5. Compare reasonable approaches.
6. Explain tradeoffs.
7. Recommend a practical next step based on the available evidence.
Do not hide uncertainty.
Bonus Prompt 51: The Ultimate Claude Opus 5.5 Master Prompt
This is a flexible prompt you can adapt to almost any serious task.
You are an expert AI assistant helping me complete a complex task.
TASK:
[DESCRIBE THE TASK]
OBJECTIVE:
[WHAT I WANT TO ACHIEVE]
CONTEXT:
[BACKGROUND INFORMATION]
INPUTS:
[DOCUMENTS / CODE / DATA / REQUIREMENTS]
CONSTRAINTS:
- [CONSTRAINT]
- [CONSTRAINT]
- [CONSTRAINT]
PRIORITIES:
1. Accuracy
2. Relevance
3. Completeness
4. Practical usefulness
5. Maintainability
6. Clear communication
WORKING APPROACH:
First understand the available information and identify important dependencies.
Do not invent missing facts.
Distinguish facts, assumptions, and recommendations.
Work through the task systematically.
When the task involves existing work, preserve useful functionality and avoid unnecessary changes.
When the task involves research, prioritize reliable and recent evidence.
When the task involves code, inspect the existing architecture before modifying it.
When the task involves writing, prioritize clarity, specificity, usefulness, and natural language.
QUALITY CHECK:
Before finishing, compare the result against every requirement.
Check for:
- missing requirements
- factual errors
- contradictions
- edge cases
- unsupported assumptions
- unnecessary complexity
- unclear sections
DEFINITION OF DONE:
The task is complete when:
[DEFINE COMPLETION]
FINAL RESPONSE:
Provide the completed result first.
Then provide:
- what was completed
- important decisions
- verification performed
- unresolved limitations
- recommended next steps, if relevant.
How to Make Claude Opus 5.5 Work Better
Use "Definition of Done"
One of the most useful ideas for advanced AI workflows is the definition of done.
Instead of:
Build my website.
Use:
The website is complete when:
- homepage is implemented
- responsive layout works
- navigation works
- contact form validates input
- error states are handled
- accessibility basics are covered
- pages load without console errors
- tests pass
- setup instructions are documented
This gives the AI an objective stopping point.
Use Context Engineering
Prompt engineering is increasingly becoming context engineering.
The question is no longer simply:
"What words should I put in my prompt?"
It is also:
"What information should the AI have before it starts?"
Useful context can include:
project documentation
previous decisions
code
customer research
spreadsheets
requirements
screenshots
design references
previous drafts
policies
technical specifications
But more context is not automatically better.
The context should be relevant.
Anthropic has reported that Claude Code sessions have increasingly involved larger context and longer-running tasks, making context management an increasingly important part of advanced AI workflows.
Claude Opus 5.5 Prompt vs Generic AI Prompt
Consider these two prompts.
Generic Prompt
Create a marketing strategy for my business.
Advanced Prompt
Create a marketing strategy for my SaaS business.
Business:
[DESCRIPTION]
Target customer:
[DESCRIPTION]
Current acquisition channels:
[CHANNELS]
Monthly budget:
[BUDGET]
Current conversion rate:
[DATA]
Goal:
[GOAL]
Create a strategy covering:
- positioning
- acquisition
- content
- paid marketing
- conversion
- retention
- measurement
For each recommendation include:
- expected objective
- required resources
- implementation difficulty
- risks
- measurement method
Separate assumptions from known facts.
Create a 30-day implementation plan.
Definition of done:
I should have a prioritized strategy, implementation roadmap, KPI framework, and list of experiments.
The second prompt gives the AI something much more valuable:
a decision environment.
Claude Opus 5.5 for Bloggers
If you run a blog, Claude Opus 5.5 can be incorporated into an entire content workflow.
A useful workflow is:
Topic discovery
↓
Search intent analysis
↓
Research
↓
Fact verification
↓
Content outline
↓
First draft
↓
Content audit
↓
SEO optimization
↓
FAQ generation
↓
Social content
↓
Final editorial review
You can even turn this into a reusable master prompt.
Claude Opus 5.5 Blogger Master Prompt
Act as my professional blogging assistant.
My website niche is:
[NICHE]
My target audience is:
[AUDIENCE]
Topic:
[TOPIC]
Create a complete publishing workflow.
First:
1. Analyze search intent.
2. Identify the reader's main problem.
3. Identify important subtopics.
4. Research the topic.
5. Separate verified facts from assumptions.
Then create:
- SEO title
- introduction
- article outline
- detailed article
- practical examples
- actionable tips
- FAQ
- conclusion
- meta description
- suggested tags
- internal-link ideas
Writing requirements:
- natural language
- useful information
- clear headings
- short readable paragraphs
- practical examples
- no keyword stuffing
- no invented facts
- no unnecessary filler
Before finishing, audit the article for:
- factual accuracy
- completeness
- search intent
- readability
- originality
- missing questions
Definition of done:
The article should be ready for editorial review and publishing.
Claude Opus 5.5 for AI Prompt Websites
If your website publishes AI prompts, you can go one step further.
Use Claude to create prompt collections, not just individual prompts.
For example:
Create a prompt library for:
[TOPIC]
Generate 50 prompts.
Organize them into:
- beginner
- intermediate
- advanced
- professional
- automation
- research
- business
- content creation
Every prompt should solve a distinct problem.
For each prompt include:
- prompt title
- use case
- copy-paste prompt
- customization fields
- expected output
- advanced variation
Avoid duplicate prompts.
This can help turn one topic into an entire content series.
Common Claude Opus 5.5 Prompting Mistakes
Mistake 1: Being Too Vague
Make my business better.
There is no clear definition of success.
Mistake 2: No Context
Fix this.
But the AI does not know what "this" means.
Mistake 3: No Constraints
If you don't specify constraints, the model may choose a solution that technically works but does not fit your project.
Mistake 4: No Verification
Always ask complex tasks to be checked against the requirements.
Mistake 5: Asking for Everything at Once Without Structure
Instead of:
Research this, write an article, make a business plan, analyze competitors, create social posts, and build a website.
Define a workflow.
Mistake 6: Confusing More Tokens With Better Results
Long prompts aren't automatically good prompts.
A concise prompt containing the correct context and constraints can outperform a huge prompt filled with repetition.
Mistake 7: Inventing Facts
When using AI for research, tell it:
Do not invent sources, statistics, quotations, or facts.
If information cannot be verified, clearly identify the uncertainty.
This is especially important for articles that will be published publicly.
Claude Opus 5.5 for Coding: A Better Workflow
For serious development work, try this pattern:
Step 1 — Understand
Inspect the repository and explain the relevant architecture.
Step 2 — Plan
Create an implementation plan without modifying unrelated components.
Step 3 — Implement
Implement the approved scope.
Step 4 — Test
Run relevant tests and identify failures.
Step 5 — Review
Review the implementation for bugs, security issues, edge cases, and unnecessary complexity.
Step 6 — Finish
Summarize the completed work and remaining limitations.
This turns an AI coding session into a controlled engineering workflow.
Claude Opus 5.5 and Long-Running Tasks
One of the important changes in modern AI development is the shift from short prompts toward longer-running tasks.
Anthropic's own developer guidance says Opus 5.5 is designed for longer coding sessions and larger amounts of context. Anthropic also reports that Claude Code sessions have become longer and increasingly involve tools and connected skills.
That means users should think less about:
"What should my next prompt be?"
And more about:
"How should I define the entire task?"
For example:
Goal:
Migrate the authentication system.
Constraints:
Preserve existing user accounts.
Requirements:
- maintain backward compatibility
- migrate sessions
- add tests
- document the migration
- provide rollback instructions
Definition of done:
All existing authentication flows work with the new implementation and the migration can be safely deployed.
This is a much stronger foundation for an extended AI session.
Claude Opus 5.5 Safety and Verification
Advanced AI models should not be treated as infallible.
Anthropic says Opus 5.5 underwent external testing before release and includes safeguards developed for its most capable models.
For important work, users should still verify outputs.
Especially verify:
financial calculations
legal documents
medical information
security decisions
production code
business-critical decisions
factual claims
statistics
citations
research conclusions
A good prompt can request verification, but verification by AI does not eliminate the need for appropriate human review.
10 Short Claude Opus 5.5 Prompts for Everyday Use
1. Improve an idea
Improve this idea without changing its core purpose:
[IDEA]
Identify the biggest weaknesses and propose practical improvements.
2. Explain something
Explain [TOPIC] to me as a beginner.
Use a simple example and then gradually introduce the technical details.
3. Find mistakes
Review this carefully and identify factual, logical, structural, and technical mistakes:
[CONTENT]
4. Make a plan
Turn this goal into a practical step-by-step plan:
[GOAL]
Include dependencies, risks, and completion criteria.
5. Summarize
Summarize this while preserving the most important facts, caveats, and conclusions:
[CONTENT]
6. Compare
Compare these options objectively:
[A]
[B]
Focus on meaningful differences, tradeoffs, limitations, and use cases.
7. Brainstorm
Generate 30 genuinely different ideas for:
[TOPIC]
Avoid variations of the same concept.
8. Rewrite
Rewrite this for clarity and naturalness without changing its factual meaning:
[TEXT]
9. Analyze
Analyze this problem systematically:
[PROBLEM]
Identify causes, evidence, options, risks, and next steps.
10. Final review
Review your previous answer against my original requirements.
Identify anything missing or incorrect and provide a corrected final version.
Claude Opus 5.5 Prompt Cheat Sheet
| Goal | Prompt Strategy |
|---|---|
| Coding | Give repository context + requirements + definition of done |
| Debugging | Provide error + code + expected behavior |
| Research | Require evidence and uncertainty labels |
| Writing | Define audience + intent + quality requirements |
| SEO | Focus on search intent and topical coverage |
| Business | Provide objective + constraints + metrics |
| Data | Ask for data-quality inspection first |
| Documents | Require evidence-based extraction |
| Long tasks | Define milestones and completion criteria |
| AI workflows | Define roles, inputs, outputs and verification |
| Creative work | Define audience, format and desired outcome |
| Decision analysis | Compare tradeoffs without hiding uncertainty |
Final Thoughts
Claude Opus 5.5 represents an important direction in AI: models are increasingly being used as workers inside larger workflows rather than simply as chatbots that answer isolated questions.
Anthropic's September 2026 release and subsequent prompting guidance emphasize complex work, longer sessions, coding, context, effort calibration, and task completion.
The most useful lesson for prompt engineering is therefore not to create increasingly complicated prompts.
Instead:
Give the AI the right context.
Define the objective.
Set clear constraints.
Explain what success looks like.
Give it relevant inputs.
Ask it to verify the result.
Define when the task is finished.
That approach makes prompts more useful across coding, research, writing, business, SEO, data analysis, and professional workflows.
And the master prompt in this article can serve as a reusable starting point for almost any serious Claude Opus 5.5 task.
Frequently Asked Questions
What is Claude Opus 5.5?
Claude Opus 5.5 is Anthropic's first Claude 5.5 model, released on September 22, 2026. Anthropic describes it as a major improvement over Opus 5 and says it performs at the level of Fable 5.1 on most work while costing 40% less to run than Opus 5.
Is Claude Opus 5.5 good for coding?
Yes. Anthropic specifically positions Opus 5.5 for demanding professional work and coding, and its documentation provides prompting guidance for long coding sessions and complex development workflows.
What is the best Claude Opus 5.5 prompt?
There is no single best prompt for every task. A strong general prompt should specify the objective, context, constraints, inputs, quality requirements, and definition of done.
Should I use very long prompts?
Not necessarily. The goal is relevant context, not maximum prompt length. Remove information that does not affect the task.
Should I tell Claude Opus 5.5 to think harder?
Anthropic's current prompting guidance says Opus 5.5 already thinks before responding, so repetitive instructions to "think harder" are not necessarily useful. More important is clearly defining the task and desired outcome.
Can Claude Opus 5.5 handle long-running tasks?
It is designed for complex and longer-running work, particularly in coding and professional workflows. Anthropic has published specific guidance on steering long runs and defining completion criteria.
Can I use these prompts for other AI models?
Yes. Most of the prompts can be adapted for other advanced AI models. You may need to modify instructions according to each model's capabilities, tools, context limits, and prompting behavior.
What is the most important prompt-engineering technique?
For complex work, clearly defining what "done" means is one of the most useful techniques. It gives the model a concrete target and makes verification easier.
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