Prevents AI hallucination by enforcing evidence-based responses with certainty and source tags during code analysis, recommendations, and confidence queries.
npx claudepluginhub joshuarweaver/cascade-code-general-misc-3 --plugin asiaostrich-universal-dev-standardsThis skill uses the workspace's default tool permissions.
> **Language**: English | [繁體中文](../../locales/zh-TW/skills/ai-collaboration-standards/SKILL.md)
Creates isolated Git worktrees for feature branches with prioritized directory selection, gitignore safety checks, auto project setup for Node/Python/Rust/Go, and baseline verification.
Executes implementation plans in current session by dispatching fresh subagents per independent task, with two-stage reviews: spec compliance then code quality.
Dispatches parallel agents to independently tackle 2+ tasks like separate test failures or subsystems without shared state or dependencies.
Language: English | 繁體中文
Version: 1.1.0 Last Updated: 2026-01-25 Applicability: Claude Code Skills
This skill is part of a three-layer AI collaboration system:
| Layer | Skill | Question it Answers | 回答的問題 |
|---|---|---|---|
| Behavior (Immediate) | /ai-collaboration (this) | "How should AI respond accurately?" | 「AI 如何準確回應?」 |
| Configuration (Session) | /ai-instruction-standards | "What to write in CLAUDE.md?" | 「CLAUDE.md 該寫什麼?」 |
| Architecture (Long-term) | /ai-friendly-architecture | "How to structure code for AI?" | 「如何讓專案對 AI 友善?」 |
This skill ensures AI assistants provide accurate, evidence-based responses without hallucination.
This skill uses two complementary tag categories:
Category 1: Certainty Tags (for analyzing existing content)
| Tag | Use When |
|---|---|
[Confirmed] | Direct evidence from code/docs |
[Inferred] | Logical deduction from evidence |
[Assumption] | Based on common patterns (needs verification) |
[Unknown] | Information not available |
[Need Confirmation] | Requires user clarification |
Category 2: Derivation Tags (for generating new content)
| Tag | Use When |
|---|---|
[Source] | Direct content from spec/requirement |
[Derived] | Transformed from source content |
[Generated] | AI-generated structure |
[TODO] | Requires human implementation |
When to Use Which:
| Workflow | Primary Tags |
|---|---|
| Code analysis | Certainty Tags |
| Reverse engineering | Certainty Tags |
| Forward derivation | Derivation Tags |
| Spec generation | Derivation Tags |
| 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 |
For complete standards, see:
[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?
The system uses Redis for caching (code not reviewed)
The UserService should have an authenticate() method (API not verified)
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.
There are three options:
1. Redis caching
2. In-memory caching
3. File-based caching
Please choose one.
Before making any statement:
[Source: Code], [Source: External], etc.?[Confirmed], [Inferred], etc.?This skill supports project-specific language configuration for certainty tags.
CONTRIBUTING.md for "Certainty Tag Language" sectionIf no configuration found and context is unclear:
CONTRIBUTING.md:## Certainty Tag Language
This project uses **[English / 中文]** certainty tags.
<!-- Options: English | 中文 -->
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
After /ai-collaboration completes, the AI assistant should suggest:
AI 協作行為規範已掌握。建議下一步 / AI collaboration behavior standards understood. Suggested next steps:
- 執行
/ai-instructions建立或更新 CLAUDE.md 等 AI 指令檔案 ⭐ Recommended / 推薦 — 將協作標準寫入專案配置 / Write collaboration standards into project configuration- 執行
/ai-friendly-architecture設計 AI 友善架構 — 從長期架構層面優化 AI 協作 / Optimize AI collaboration at the architecture level- 執行
/review運用確定性標籤進行程式碼審查 — 實踐基於證據的分析 / Practice evidence-based analysis
| Version | Date | Changes |
|---|---|---|
| 1.1.0 | 2026-01-25 | Added: Unified Tag System with Certainty and Derivation tag categories |
| 1.0.0 | 2025-12-24 | Added: Standard sections (Purpose, Related Standards, Version History, License) |
This skill is released under CC BY 4.0.
Source: universal-dev-standards