Assemble AI agent prompts from ordered modules with token budget management.
npx skills add https://github.com/project-ax/ax --skill prompt-builder-project-ax
Please help me install this Agent Skill. Skill: prompt-builder Source: https://github.com/project-ax/ax/tree/main/.claude/skills/ax/prompt-builder Command: npx skills add https://github.com/project-ax/ax --skill prompt-builder-project-ax
This Skill addresses the complexity of dynamically assembling and managing the instructions given to an AI agent, ensuring optimal performance and resource utilization.
Use the prompt-builder skill to add a new module for handling user preferences to the agent's prompt.
High-intent search queries and answers about installing and using this skill.
You dynamically assemble AI agent system prompts by processing ordered modules through a pipeline that manages conditional inclusion. This ensures the final prompt is contextually structured and optimized for the agent's operational requirements.
Managing token budgets when building LLM instructions involves intelligently including or dropping composable modules based on the available context window. This guarantees the assembled system prompt stays within operational token allocation limits without manual truncation.
Initial identity discovery for a new AI agent is set up using bootstrap mode. This mode manages the initial agent setup process, allowing the system to dynamically discover and establish the agent's core identity before full prompt assembly begins.
Yes, you can conditionally include specific tool instructions in an LLM prompt. The module system supports conditional inclusion based on available context tokens and produces context-aware tool filtering metadata to control exactly which instructions are active.
Prompt engineering works effectively with modular systems for multi-feature agent development by allowing you to add new modules for specific features like user preferences. Each module defines specific instructions and ensures they are prioritized correctly within the overall prompt.
mehdicExecute prompt_builder.py to generate agent prompts with token budgets.
dbowm91Load and activate markdown-defined agent skills from project directories.
CarbeneAIOptimize prompts and context to reduce noise and improve LLM outputs.
kolbickBundle natural language prompts with project files into a single AI input.
