goal-meta-skill

Transform ambiguous user requirements into structured /goal commands for Claude Code and Codex.

16|1|Updated Jan 2, 2026
One-click install
npx skills add https://github.com/bahayonghang/my-ai-cli-toolkit --skill goal-meta-skill
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: goal-meta-skill
Source: https://github.com/bahayonghang/my-ai-cli-toolkit/tree/main/skills/developer-tools-integrations/goal-meta-skill
Command: npx skills add https://github.com/bahayonghang/my-ai-cli-toolkit --skill goal-meta-skill

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires python, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill solves the issue of vague, unmanageable AI agent tasks by transforming them into structured, verifiable, and bounded goal contracts that prevent agent failure and scope creep.

Core Features & Use Cases

  • Platform-Specific Goal Generation: Creates optimized /goal instructions for both Claude Code and Codex.
  • Safety & Verification: Automatically injects verification evidence, write boundaries, and stop/pause conditions to ensure safe execution.
  • Use Case: If you have a vague requirement like "make this app better," this Skill converts it into a concrete task with specific success criteria, iteration policies, and safety guardrails, ensuring the agent knows exactly when to stop and when to ask for human input.

Quick Start

Use the goal-meta-skill to turn my request for a new browser-based game into a safe and verifiable goal command.

Frequently Asked Questions about goal-meta-skill

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

FAQPage Schema
How do I convert vague requirements into structured agent commands for Claude Code?

To convert vague requirements into structured agent commands for Claude Code, this Skill transforms ambiguous user requests into verifiable, bounded goal contracts. It defines outcome-based objectives, write boundaries, and explicit stop conditions to ensure safe execution.

What is the best way to prevent scope creep when assigning tasks to Codex agents?

The best way to prevent scope creep with Codex agents is to enforce turn-based bounding clauses and transcript-visible proof requirements. This Skill injects these safety guardrails automatically, ensuring the agent stops and asks for human input when necessary.

How to write executable goal commands with verification evidence for AI agents?

You write executable goal commands with verification evidence by specifying outcome-based objectives and requiring transcript-visible proof. This Skill generates these structured /goal instructions, embedding iteration policies and verification criteria directly into the prompt.

Does this goal generation approach work with both Claude Code and Codex platforms?

Yes, this goal generation approach works with both Claude Code and Codex platforms. It provides platform-specific goal generation, creating optimized /goal instructions tailored to the distinct execution environments of each AI agent platform.

Why do my AI agents fail or lose focus when executing open-ended software engineering tasks?

AI agents fail or lose focus on open-ended software engineering tasks due to vague, unmanageable instructions lacking explicit stop or pause conditions. This Skill solves this by structuring tasks into verifiable goal contracts with strict write boundaries.

Do I need Python to generate structured goal contracts for my prompts?

Yes, you need Python installed to run the scripts that generate structured goal contracts. The Skill relies on Python components to transform ambiguous requirements into precise, executable /goal commands with safety guardrails.