Prompt Naming Convention
Consistent naming makes prompts searchable and scannable. The three-part structure (category, action, specificity) balances brevity with discoverability across large libraries.
Use the following naming convention for all prompts in our library: Format: [Category] - [Action] - [Specificity] Examples: - "Writing - Blog Post - Technical Tutorial" - "Code - Review - Python Security Audit" - "Analysis - Competitor - Quarterly Summary" - "Support - Reply - Refund Request" Rules: 1. Category must be one of: {{categories}} 2. Action should be a verb or verb phrase describing what the prompt does 3. Specificity narrows the use case so the prompt is findable 4. Maximum 60 characters total 5. Use title case, separated by hyphens Apply this convention to the following prompt: Title: "{{current_title}}" Purpose: {{purpose}} Suggested name:
Variables to customize
Why this prompt works
Consistent naming makes prompts searchable and scannable. The three-part structure (category, action, specificity) balances brevity with discoverability across large libraries.
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.