ax-go-agent-context

Select Go Ax mechanisms for agent context, memory, optimization, and trajectory policy.

2.9k|186|Updated Feb 23, 2023
One-click install
npx skills add https://github.com/ax-llm/ax --skill ax-go-agent-context
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ax-go-agent-context
Source: https://github.com/ax-llm/ax/tree/main/website/static/go/.well-known/agent-skills/ax-go-agent-context
Command: npx skills add https://github.com/ax-llm/ax --skill ax-go-agent-context

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps you decide how a Go Ax agent should handle context so you can avoid mixing short-lived run state with long-term memory, optimization artifacts, or trajectory policies.

Core Features & Use Cases

  • Context Selection: Choose between context maps, context policy, offline optimization, and recall for long-context agent work.
  • Go Package Guidance: Write against the generated Go package API and examples instead of TypeScript-only interfaces.
  • Agent Design Scenarios: Use it when building agents that need memory, delegation, runtime profiles, or optimizer-aware behavior.
  • Guardrails and Validation: Follow package facts, runtime profile constraints, and AxIR source-of-truth guidance to keep implementations aligned.
  • Use Case: A developer building a long-running support assistant can use this Skill to determine whether a question belongs in context maps, a policy layer, or a recall and optimization workflow.

Quick Start

Ask the assistant to use the ax-go-agent-context skill to choose the correct Go Ax feature for your long-context agent design and explain why.

Frequently Asked Questions about ax-go-agent-context

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

FAQPage Schema
How do I choose between context maps, recall, and optimization for a Go agent?▼

To choose the right Go agent context path, evaluate whether your agent needs context maps for run state, recall for long-term memory, context policy for rules, or offline optimization for trajectory evaluation.

What is the difference between context policy and long-term memory in Go Ax agents?▼

Context policy governs runtime agent behavior and delegation constraints, whereas long-term memory utilizes recall mechanisms to persist information across sessions without contaminating short-lived run state or optimization artifacts.

How do I implement long-context agent memory using generated Go Ax packages?▼

Implement long-context agent memory by writing against the generated Go package APIs and examples, using AxIR-generated interfaces to align runtime profiles, context maps, and recall workflows with source-of-truth package facts.

Can I use Ax offline optimization and replay workflows for Go agents?▼

Yes, you can use Ax offline optimization and replay workflows with Go agents by selecting the appropriate trajectory policy mechanism to evaluate and refine long-context agent behavior without affecting live runtime profiles.

When should I separate agent run state from trajectory policies in Go?▼

You should separate agent run state from trajectory policies when building long-running agents to avoid mixing short-lived execution data with offline optimization artifacts, ensuring runtime profiles remain aligned with AxIR package constraints.