aif-grounded

Enforce evidence-based reasoning and a 100/100 confidence gate before delivering answers.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/ichinya/idshka --skill aif-grounded-ichinya
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: aif-grounded
Source: https://github.com/ichinya/idshka/tree/main/.codex/skills/aif-grounded
Command: npx skills add https://github.com/ichinya/idshka --skill aif-grounded-ichinya

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill enforces a strict reliability gate for AI outputs, ensuring answers are evidence-based and only delivered when confidence is 100/100.

Core Features & Use Cases

  • Confidence gate: delivers final results only when evidence supports 100/100 confidence.
  • Uncertainty handling: returns a concise "what's missing" checklist instead of guesses if confidence is below 100.
  • High-stakes applicability: ideal for security, legal, finance, medical-adjacent tasks or any scenario requiring verifiable accuracy.

Quick Start

Apply the grounded reliability gate to a user query to ensure only 100% confident results are delivered.

Frequently Asked Questions about aif-grounded

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

FAQPage Schema
How do I enforce evidence-based reasoning and prevent AI guessing on high-stakes queries?

You enforce evidence-based reasoning by applying a strict confidence gate that delivers final results only when 100/100 confidence is met. If evidence is insufficient, it returns a concise checklist of missing information instead of a guess.

What happens when AI confidence is below 100% for sensitive tasks?

When AI confidence is below 100%, the system returns a concise "what's missing" checklist instead of guessing. This uncertainty handling ensures you know exactly what evidence is required to reach full confidence.

Can I use a confidence gate for security, legal, and finance queries?

Yes, the confidence gate is ideal for security, legal, finance, and medical-adjacent tasks. It ensures high-stakes applicability by demanding verifiable accuracy and explicit uncertainty handling before any final answer is delivered.

What is the best way to handle AI uncertainty and demand explicit confidence?

The best way to handle AI uncertainty is implementing a 100/100 confidence gate that blocks unverified answers. This approach grounds outputs in evidence and forces explicit uncertainty checks for high-stakes tasks.

When do I need an evidence-based reliability gate for AI outputs?

You need an evidence-based reliability gate when working with high-stakes, sensitive queries requiring 100% confidence. It prevents guessing by enforcing strict reliability checks and returning missing data checklists for incomplete evidence.