Analyze Entire Project Libraries with 1M Token Context and Adaptive Thinking
Use Claude Fable 5 to analyze massive document sets in one go.
Leverage the 1M token context window and adaptive thinking of Claude Fable 5 to process entire document repositories without manual chunking.
The Scenario
You have a folder containing six months of internal meeting transcripts and project specs. You need to identify every time a specific budget decision was mentioned and why it changed.
Before & after
Manually reviewing dozens of long legal documents or technical manuals would take a desk worker 6–8 hours and often lead to 'context fatigue' or missed details.
Using Claude Fable 5, the model uses 'adaptive thinking' to automatically adjust its reasoning depth. This allows you to process 1M tokens of data with high accuracy in 2–4 minutes.
The Prompt
I am providing a massive dataset/collection of documents: [PASTE_ALL_DOCUMENTS_OR_TEXT]. Using your adaptive thinking and 1M token context, please synthesize a comprehensive report that identifies [SPECIFIC_TREND_OR_DATA_POINT] and highlights any contradictions between these sources.
Claude Fable 5 and Mythos 5 now support a massive 1 million token context window by default. This is paired with 'adaptive thinking,' which allows the model to dynamically scale its reasoning effort based on the complexity of the input. Use this for 'needle in a haystack' tasks across entire project libraries.
Source
Claude Platform - Claude API Docs"Both models support a 1M token context window by default, 128k max output tokens, and always-on adaptive thinking."