valuate

Adjust AI agent operational parameters and characteristic states via conversation.

Updated Aug 23, 2026

Search Tags:#state management #configuration #ai behavior #agent tuning #operational modes #parameter adjustment

Ready to run

npx skills add https://github.com/bert-berkers/UrbanRepML --skill valuate

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: valuate
Source: https://github.com/bert-berkers/UrbanRepML/tree/main/.claude/skills/valuate
Command: npx skills add https://github.com/bert-berkers/UrbanRepML --skill valuate

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill allows users to precisely control the operational parameters and characteristic states of AI agents, ensuring they align with specific task requirements and strategic goals.

Core Features & Use Cases

Dynamic State Adjustment: Modify parameters like execution speed, code quality, and exploration vs. exploitation balance.
Mode Selection: Switch between operational modes such as 'exploratory', 'focused', 'sprint', and 'creative'.
Use Case: Before starting a complex coding task, you can use this Skill to set the mode to 'focused', increase 'code quality' to 5, and decrease 'execution speed' to 2, ensuring a meticulous and high-quality output.

Quick Start

Use the valuate skill to set the mode to sprint and execution speed to 5.

Frequently Asked Questions about valuate

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I adjust AI agent behavior for specific coding tasks?▼

Adjust AI agent behavior by modifying characteristic states and operational parameters like execution speed, code quality, and exploration balance through a conversational interface. You can set specific modes such as 'focused' or 'sprint' to align agent execution with your task requirements.

What are operational modes for tuning multi-agent system states?▼

Operational modes for tuning multi-agent system states include 'exploratory', 'focused', 'sprint', and 'creative'. Switching between these modes allows you to control the strategic direction and execution style of AI agents within your system.

Can I save and load agent profiles for session-specific context?▼

Yes, you can save and load agent profiles to preserve operational parameter configurations. This integrates with temporal priors to provide session-specific context, ensuring your adjusted execution speed and code quality settings persist across different tasks.

How do I set AI agent execution speed and code quality parameters?▼

Set AI agent execution speed and code quality parameters through a conversational tuning interface. For example, you can request the system to increase code quality to 5 and decrease execution speed to 2 to ensure meticulous, high-quality output for complex tasks.

When should I switch AI agents to exploratory mode versus focused mode?▼

Switch AI agents to exploratory mode when prioritizing broad solution discovery, and use focused mode for complex coding tasks requiring meticulous output. Adjusting the exploration-vs-exploitation balance ensures the agent's operational state matches your strategic goals.

Does this parameter adjustment require external dependencies?▼

No, this parameter adjustment requires no external dependencies to tune AI agent behavior. It operates independently to facilitate state management and modify operational dimensions directly within your existing multi-agent system architecture.