Token Counter
Structured table output forces the model to quantify each section, making waste immediately visible.
Analyze the following text and provide a detailed token breakdown:\n\n{{text}}\n\nFor each section, report:\n1. Approximate token count (using GPT-4 tokenization rules)\n2. Percentage of total tokens consumed\n3. Which sections could be compressed without losing meaning\n\nFormat the output as a table with columns: Section | Tokens | % of Total | Compressible (Y/N)Variables to customize
Why this prompt works
Structured table output forces the model to quantify each section, making waste immediately visible.
Save this prompt to your library
Organize, version, and access your best prompts across ChatGPT, Claude, and Cursor.
Related prompts
Forcing the agent to plan before acting prevents premature execution and wasted steps. Explicit dependency mapping enables parallel execution and catches logical gaps early.
Tool Selection AgentThe ReAct pattern (Reason + Act) creates an explicit reasoning trace that improves tool selection accuracy. The error-handling rule prevents infinite retry loops.
Prompt CompressorExplicitly requiring all functional requirements to be preserved prevents the model from over-compressing and losing critical instructions.
Memory Management AgentExplicit memory read/write instructions create agents that improve over time. Categorization keeps memories organized, and the deduplication rule prevents context bloat.