evidence-standards

Name: evidence-standards
Availability: InStock
Author: faisalanjum

Enforce source-only, exact, and traceable data rules for sub-agents.

3|1|Updated Dec 2, 2024

Search Tags:#data integrity #traceability #data governance #anti-hallucination #agent guardrails #reporting standards

Ready to run

npx skills add https://github.com/faisalanjum/EventTrader --skill evidence-standards

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: evidence-standards
Source: https://github.com/faisalanjum/EventTrader/tree/main/.claude/skills/evidence-standards
Command: npx skills add https://github.com/faisalanjum/EventTrader --skill evidence-standards

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill establishes strict rules for data sub-agents to prevent hallucinations and ensure all returned data can be traced back to its original source, enhancing data reliability.

Core Features & Use Cases

Source-Only Data: Enforces that only data present in the tool's output is returned.
Exact Values: Mandates that data is returned without rounding or paraphrasing.
Traceability: Requires clear source references for all data points.
Derived Values Handling: Ensures computed values are marked and their inputs cited.
Domain Boundary Enforcement: Keeps agents within their designated operational scope.

Quick Start

Apply these evidence standards to all data sub-agents to guarantee source-only, exact, and traceable data reporting.

Frequently Asked Questions about evidence-standards

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

FAQPage Schema

How do I prevent AI agent hallucinations and enforce data traceability in reporting?▼

To prevent AI agent hallucinations and enforce data traceability, apply strict evidence standards that mandate agents return only source data, use exact values, and provide stable source references for all reported information.

What rules ensure data sub-agents return exact values without modification from query outputs?▼

Rules ensuring data sub-agents return exact values mandate that agents extract only data present in tool outputs without rounding or paraphrasing, and enforce domain boundaries to keep operations within designated scopes.

How do you handle derived values and computed data in agent governance frameworks?▼

Handling derived values in agent governance frameworks requires explicitly marking computed values and citing their original input sources to maintain full traceability and prevent hallucinated data reporting.

Can I enforce domain boundaries to keep data agents within their designated operational scope?▼

Yes, you can enforce domain boundaries to keep data agents within their designated operational scope, preventing unauthorized data access and ensuring agents only process information relevant to their specific domain.

What is source traceability in data governance and when do I need it for sub-agents?▼

Source traceability in data governance ensures every data point returned by sub-agents can be traced back to its original source, which is needed whenever reliable, verifiable data reporting is required.

Are there limitations to enforcing reporting standards on data sub-agents?▼

Limitations of enforcing reporting standards include potential rigidity in handling ambiguous data sources, requiring clearly defined domain boundaries and structured tool outputs to function effectively without modification.