aif-grounded

Enforces evidence-based answers with a confidence gate that blocks unverified claims.

Updated Jun 5, 2026
One-click install
npx skills add https://github.com/1t1sCooL/zazyvala-bot --skill aif-grounded-1t1scool
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: aif-grounded
Source: https://github.com/1t1sCooL/zazyvala-bot/tree/main/.cursor/skills/aif-grounded
Command: npx skills add https://github.com/1t1sCooL/zazyvala-bot --skill aif-grounded-1t1scool

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? AI assistants often guess or fabricate answers when information is missing, which is dangerous for high-stakes questions involving versions, security, finance, or legal topics. This Skill acts as a reliability gate that forces every claim to be backed by verifiable evidence or returns an explicit "insufficient information" result instead of a guess. ## Core Features & Use Cases - Request Classification: Sorts each request into repo-grounded, doc-grounded, or external-facts categories so the right evidence standard is applied. - Confidence Gate: Computes a 0-100 confidence score and only delivers a final answer at 100, otherwise outputs a structured list of missing evidence and concrete steps to reach full confidence. - Changeable-Fact Verification: Mandates verification of volatile facts like "latest version" or "current default" against authoritative docs, release notes, or logs before answering. - Use Case: When asked "does library Y support feature Z in the latest release?", the Skill refuses to guess, lists exactly which docs or command outputs are needed, and only answers once the evidence is provided. ## Quick Start Ask the assistant to answer a high-stakes question only if it is 100 percent sure based on verifiable evidence, with no assumptions or hallucinations.

Frequently Asked Questions about aif-grounded

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

FAQPage Schema
How do I stop an AI assistant from hallucinating answers?

Use a reliability gate that requires every factual claim to be backed by evidence from repository files, command outputs, or provided documents. If any claim lacks support, the assistant returns an insufficient-information result listing exactly what evidence is missing instead of guessing.

How to verify facts about latest library versions before answering?

Classify the request as external-facts, then verify against authoritative docs, release notes, or logs before answering. If verification is impossible with available tools, return insufficient information and ask the user for the specific source excerpt or version output.

What is a confidence gate in AI-assisted workflows?

A confidence gate is a scoring mechanism where an answer is only delivered at 100 out of 100 confidence, meaning every claim is evidence-backed with no open unknowns. Below that threshold, the system outputs missing evidence and concrete steps to reach full confidence.

When should an AI refuse to answer instead of guessing?

Refusal is appropriate for high-stakes domains like security, finance, legal, or medical questions, and whenever changeable facts cannot be verified. The Skill returns a structured checklist of missing evidence rather than a fabricated answer.

Can this approach be used for code changes in a repository?

Yes, but patches are only applied once confidence reaches 100, meaning requirements are precise and build or test verification is possible. If the repo lacks a verification path, the Skill proposes the minimal validation needed instead of implementing blindly.