GPT-4o
⚙️ Technical
Basic
Long-Context Document Analysis
Use million-token context AI models to analyze entire documents, codebases, or research collections and extract structured insights in one pass.
The Prompt
# Long-Context Document Analysis You are an AI systems specialist. Design a long-context analysis workflow for [DOCUMENT SET, e.g. a 500-page legal filing, an entire codebase, a year of earnings call transcripts]. ## Context Setup - Model to use: [MODEL, e.g. Claude Fable 5.1, GPT-6 Astra, Gemini 3.8 Flash] - Context window available: [TOKENS] - Document size: [APPROXIMATE SIZE] ## Analysis Goal What are you trying to extract or answer? [ANALYSIS OBJECTIVE, e.g. identify all risk clauses, find all references to a specific topic, summarize the key arguments] ## Prompt Structure Design the system prompt and user prompt for this analysis. Include instructions for: - How to handle ambiguous sections - Output format (JSON / markdown / plain prose) - How to flag low-confidence findings ## Chunking Strategy (if needed) If the document exceeds the context window, describe how to split, process, and merge chunk outputs. ## Verification Step How do you validate that the model has not missed sections or hallucinated references?
📝 Fill in the blanks
Replace these placeholders with your own content:
[DOCUMENT SET, e.g. a 500-page legal filing, an entire codebase, a year of earnings call transcripts]
[MODEL, e.g. Claude Fable 5.1, GPT-6 Astra, Gemini 3.8 Flash]
[TOKENS]
[APPROXIMATE SIZE]
[ANALYSIS OBJECTIVE, e.g. identify all risk clauses, find all references to a specific topic, summarize the key arguments]
How to use this prompt
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2
Replace the placeholders
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3
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