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ai-collaboration-standards

Enforce evidence-based code analysis with certainty tags and source citations.

5|1|Updated Jan 14, 2026
Search Tags:#collaboration#transparency#evidence#code-analysis#certainty#anti-hallucination#source-citation
One-click install
npx skills add https://github.com/ValorVie/custom-skills --skill ai-collaboration-standards-valorvie
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ai-collaboration-standards
Source: https://github.com/ValorVie/custom-skills/tree/main/skills/ai-collaboration-standards
Command: npx skills add https://github.com/ValorVie/custom-skills --skill ai-collaboration-standards-valorvie

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Prevents AI hallucination by enforcing evidence-based reasoning, explicit sourcing, and transparent justification when analyzing code or making recommendations.

Core Features & Use Cases

  • Enforces explicit source-citing with a unified certainty tag system (e.g., [Confirmed], [Inferred], [Assumption], [Unknown], [Need Confirmation]).
  • Provides anti-hallucination guidelines and structured reasoning templates to improve reliability across code analysis, review, and documentation tasks.
  • Supports cross-project collaboration by standardizing how conclusions are presented, cited, and validated.

Quick Start

Provide a source-backed answer for code analysis tasks by applying the standardized certainty tags.

Frequently Asked Questions about ai-collaboration-standards

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

FAQPage Schema
How do I prevent AI hallucination during code analysis and recommendations?▼

To prevent AI hallucination during code analysis, apply evidence-based reasoning standards that enforce explicit source citation and transparent justification for all generated conclusions and recommendations.

What are certainty tags for transparent AI code review?▼

Certainty tags for transparent AI code review are standardized labels like Confirmed, Inferred, Assumption, and Unknown, used to explicitly classify the derivation and reliability of each AI-generated analytical conclusion.

How to standardize source citation rules for cross-project AI collaboration?▼

Standardize source citation rules for cross-project AI collaboration by applying a unified certainty tagging system that requires explicit source backing and structured reasoning templates for all code analysis outputs.

Does evidence-based AI collaboration work with existing Claude Code workflows?▼

Evidence-based AI collaboration standards apply directly across Claude Code workflows, integrating anti-hallucination protocols and certainty tagging into code analysis, review, option provision, and documentation tasks.

What are the limitations of certainty tagging for anti-hallucination in AI?▼

Certainty tagging limitations include relying on the AI's ability to accurately self-classify its derivations as Confirmed or Inferred, which requires sufficient source context to avoid mislabeling assumptions as confirmed facts.

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