AI Collaboration Standards

This skill ensures AI assistants provide accurate, evidence-based responses without hallucination.

Quick Reference

Certainty Tags

Tag	Use When
[Confirmed] / [已確認]	Direct evidence from code/docs
[Inferred] / [推論]	Logical deduction from evidence
[Assumption] / [假設]	Based on common patterns (needs verification)
[Unknown] / [未知]	Information not available
[Need Confirmation] / [待確認]	Requires user clarification

Source Types

Source Type	Tag	Reliability
Project Code	[Source: Code]	⭐⭐⭐⭐⭐ Highest
Project Docs	[Source: Docs]	⭐⭐⭐⭐ High
External Docs	[Source: External]	⭐⭐⭐⭐ High
Web Search	[Source: Search]	⭐⭐⭐ Medium
AI Knowledge	[Source: Knowledge]	⭐⭐ Low
User Provided	[Source: User]	⭐⭐⭐ Medium

Core Rules

1. Evidence-Based Only: Only analyze content that has been explicitly read
2. Cite Sources: Include file path and line number for code references
3. Classify Certainty: Tag all statements with certainty level
4. Always Recommend: When presenting options, include a recommended choice with reasoning

Detailed Guidelines

For complete standards, see:

• Anti-Hallucination Guidelines
• Certainty Labels Reference

Examples

✅ Correct Response

[Confirmed] src/auth/service.ts:45 - JWT validation uses 'jsonwebtoken' library
[Inferred] Based on repository pattern in src/repositories/, likely using dependency injection
[Need Confirmation] Should the new feature support multi-tenancy?

❌ Incorrect Response

The system uses Redis for caching (code not reviewed)
The UserService should have an authenticate() method (API not verified)

✅ Correct Option Presentation

There are three options:
1. Redis caching
2. In-memory caching
3. File-based caching

**Recommended: Option 1 (Redis)**: Given the project already has Redis infrastructure
and needs cross-instance cache sharing, Redis is the most suitable choice.

❌ Incorrect Option Presentation

There are three options:
1. Redis caching
2. In-memory caching
3. File-based caching

Please choose one.

Checklist

Before making any statement:

• Source Verified - Have I read the actual file/document?
• Source Type Tagged - Did I specify [Source: Code], [Source: External], etc.?
• Reference Cited - Did I include file path and line number?
• Certainty Classified - Did I tag as [Confirmed], [Inferred], etc.?
• No Fabrication - Did I avoid inventing APIs, configs, or requirements?
• Recommendation Included - When presenting options, did I include a recommended choice?

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Configuration Detection

This skill supports project-specific language configuration for certainty tags.

Detection Order

1. Check CONTRIBUTING.md for "Certainty Tag Language" section
2. If found, use the specified language (English / 中文)
3. If not found, default to English tags

First-Time Setup

If no configuration found and context is unclear:

1. Ask the user: "This project hasn't configured certainty tag language preference. Which would you like to use? (English / 中文)"
2. After user selection, suggest documenting in CONTRIBUTING.md:

## Certainty Tag Language

This project uses **[English / 中文]** certainty tags.
<!-- Options: English | 中文 -->

Configuration Example

In project's CONTRIBUTING.md:

## Certainty Tag Language

This project uses **English** certainty tags.

### Tag Reference
- [Confirmed] - Direct evidence from code/docs
- [Inferred] - Logical deduction from evidence
- [Assumption] - Based on common patterns
- [Unknown] - Information not available
- [Need Confirmation] - Requires user clarification

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License: CC BY 4.0 | Source: universal-doc-standards