Opc_Kit

作者 sacrtap已验证

Opc_Kit is a cross-platform AI Agent skill toolkit. Each skill is a meticulously designed, rigor validated professional workflow that helps product managers, developers, and designers efficiently complete complex tasks.

4
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1
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Python
语言
2026/8/24
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⚠️ 第三方软件声明

本 Skill 为第三方开源软件,独立托管于 GitHub。SkillTip 仅为信息目录,不控制或维护底层仓库。所显示的安全检查为自动化且范围有限,安装前请自行审查源码。

阅读服务条款

安装

添加到你的 Claude Code skills 目录:

# Add to your Claude Code skills
git clone https://github.com/sacrtap/Opc_Kit

快速入门

使用 Opc_Kit 等 Skills 的指南。

安全报告

已验证

上次扫描:—

{
  "status": "PASSED",
  "issues": []
}

README.md

Opc_Kit

Professional AI Agent Skill Toolkit — From multi-persona decision debates to structured PRD output, a complete product workflow solution compatible with all AI coding agents

License: MIT Version: v2.5.1 Status: Active skills.sh PRD Validation


Why Opc_Kit?

Most AI tools give you a single perspective. Opc_Kit gives you a complete product decision loop.

  • From Debate to Document — Use party-mode to simulate expert roundtables, then create-prd to turn decisions into structured, production-ready PRDs. Two skills, one seamless workflow.
  • Eliminate Blind Spots — 17 professional personas covering engineering, product, and strategy challenge your assumptions before you write a single requirement.
  • Professional-Grade Quality — Bidirectional traceability, first-principles validation, and 7-dimension scoring ensure every output meets senior PM standards.
  • Zero Learning Curve — Natural language triggers with automatic intent detection. No commands to memorize, no configuration needed.
  • Universal Compatibility — One skill set works across all AI coding agents with automatic tool adaptation. No vendor lock-in.

Skills Overview

SkillPurposeVersionQuick InstallGuide
📝 create-prdPRD creation, update & validationv2.5.1npx skills add sacrtap/Opc_Kit --skill create-prdUsage Guide
🎭 party-modeMulti-persona product decision discussionv1.0.0npx skills add sacrtap/Opc_Kit --skill party-modeUsage Guide

Quick Start

Installation

# Install all skills
npx skills add sacrtap/Opc_Kit

# Install specific skill
npx skills add sacrtap/Opc_Kit --skill create-prd
npx skills add sacrtap/Opc_Kit --skill party-mode

# List available skills
npx skills add sacrtap/Opc_Kit --list

Basic Usage

Use create-prd alone:

/create-prd Write a PRD for user authentication feature

Use party-mode alone:

/party-mode — Should we use microservices or monolith? We're a 5-person team at MVP stage.

Complete workflow: debate first, then document

# Step 1: Stress-test the idea from multiple perspectives
/party-mode — Should we build a real-time collaboration feature for our document editor?
Tech stack: React + Node.js. Scale: 5K concurrent users. Timeline: 8 weeks.

# Step 2: Turn the decision into a structured PRD
/create-prd Based on the party-mode discussion, write a PRD for real-time collaboration

Two skills, one seamless workflow: from multi-perspective debate to actionable documentation.


Skill Highlights

📝 create-prd — Professional PRD Writing Assistant

Transform product requirements into structured, production-ready documents with enterprise-grade quality assurance.

Key Features:

  • 13-Chapter Standard Template — Fixed skeleton ensuring completeness, from problem description to risk analysis
  • Bidirectional Traceability — US↔FR 1:1 mapping, every feature traces back to a user story
  • Dual-Mode Workflow — Coaching mode (guided interaction, ~5-10 min) or Fast mode (direct generation, ~2-3 min)
  • 7-Dimension Quality Scoring — Quantitative assessment with production-ready benchmarks (70+ = ready, 85+ = excellent)
  • Exception-Covered Flowcharts — Mermaid diagrams with mandatory failure/timeout branches for all external calls
  • Auto Language Detection — Chinese/English bilingual support with intelligent switching

Example Output:

User: /create-prd Help me write a PRD for user collection feature

Result:
✅ 13-chapter PRD with bidirectional traceability
✅ Mermaid flowcharts with exception paths
✅ Quality score: 82/100 (production-ready)
✅ Assumption index with 5 tagged inferences

📚 Read the full guide for detailed features, templates, and methodology.


🎭 party-mode — Multi-Persona Decision Discussions

Stop making critical decisions with a single perspective. Bring 17 product and engineering experts into real debates around your questions — not a pros/cons list, but a room of experts who argue, challenge assumptions, and push toward defensible conclusions.

Use it when the cost of being wrong is high:

ScenarioWhat You Get
New product (0→1)Stress-test market hypotheses, validate willingness-to-pay, identify real moats before committing resources
Key feature designCatch UX gaps, security risks, scaling issues, and delivery blind spots before development starts
Architecture decisionsDebate irreversible choices with multiple experienced architects evaluating your specific constraints
Product roadmapEvidence-based prioritization across competing priorities with multi-lens challenge
Business modelUnit economics validation, GTM strategy evaluation, long-term defensibility assessment

Key Features:

  • 17 Professional Personas — Engineering, product, and strategy experts with distinct expertise and communication styles
  • Dynamic Role Selection — Auto-selects 4-6 most relevant experts based on your topic
  • Three Discussion Tiers — Quick Take (3-5 rounds), Standard (8-12 rounds), Deep Dive (15-25 rounds) based on complexity
  • Four Operating Modes — Subagent (independent thinking), Session (lightweight), Auto (hybrid), Agent-Team (persistent)
  • Evidence-Driven — Roles cite industry data, benchmarks, and case studies, not just opinions
  • Session Memory — Cross-session context retention, roles remember previous conclusions and alliances

Example:

/party-mode — We're building an AI habit tracking app. Target: professionals 25-40.
Hypothesis: $8/month for AI coaching. Budget: $200K, 4-person team, 6-month runway.

You'll hear:
- Cai challenging the $8/month assumption with real ARPU data for habit apps
- Ren asking if you've talked to 20 target users about their actual pain points
- Tao proposing a 2-week WhatsApp validation test before writing any code
- Wei warning that AI personalization is not a moat — every app will add GPT in 6 months
- Splinter questioning whether your target demo is even the right demographic

📚 Read the full guide for detailed scenarios, all personas, and advanced features.


Cross-Platform Compatibility

Skills are platform-agnostic by design. They use natural language instructions and generic tool descriptions that any AI coding agent can interpret and execute. No vendor lock-in, no configuration needed.

Verified Platforms

PlatformStatusNotes
OpenCode✅ Full supportNative skill system, subagent support
Claude Code✅ Full supportNative skill system, subagent support
Cursor✅ Full supportBuilt-in tools, inline chat
Codex✅ Full supportCLI-based, full tool access
GitHub Copilot✅ CompatibleWorkspace mode, chat interface
Windsurf (Codeium)✅ CompatibleCascade flow, chat mode
Aider✅ CompatibleChat-based interaction
Cline✅ CompatibleVS Code extension, full tool access
Continue✅ CompatibleOpen-source, configurable
JetBrains AI✅ CompatibleIDE-integrated assistant
Amazon Q Developer✅ CompatibleCLI and IDE integration
Google Jules✅ CompatibleAgent-based workflow
Zed AI✅ CompatibleBuilt-in AI assistant
Void✅ CompatibleOpen-source alternative
Trae✅ CompatibleIDE-integrated assistant

How It Works

Skills follow a universal design pattern:

  • Natural language instructions — Any LLM can understand the workflow
  • Generic tool descriptions — "Read file", "Write file", "Search content" instead of tool-specific APIs
  • Automatic fallback — When a feature isn't available (e.g., subagents), skills adapt gracefully
  • No configuration — Just install and use, skills detect capabilities automatically

Adding Support for Your Platform

If your preferred AI tool isn't listed, skills will likely work out of the box. The key requirements:

  1. The agent can read and write files
  2. The agent can execute bash/shell commands
  3. The agent supports multi-turn conversations

That's it. No special integration needed.


Contributing

We welcome high-quality skill contributions!

Adding New Skills

  1. Fork this repository
  2. Create new skill folder (e.g., my-skill/)
  3. Write SKILL.md following our structure guidelines
  4. Submit PR with usage examples

Skill Quality Standards

  • ✅ Fixed template + mandatory validation mechanism
  • ✅ Recommendation-driven interaction (not fill-in-the-blank Q&A)
  • ✅ Bidirectional traceability assurance
  • ✅ Professional perspective + industry best practices
  • ✅ Cross-platform compatible (no Agent toolchain lock-in)
  • ✅ Complete documentation + usage examples

License

MIT © sacrtap


Community


Opc_Kit — Empower AI Agents to become true product workflow experts, not simple Q&A machines.

常见问题

What is Opc_Kit?

Opc_Kit is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by sacrtap. Opc_Kit is a cross-platform AI Agent skill toolkit. Each skill is a meticulously designed, rigor validated professional workflow that helps product managers, developers, and designers efficiently complete complex tasks. It has 4 GitHub stars.

Is Opc_Kit safe to use?

Yes. Opc_Kit passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.

How do I install Opc_Kit?

Clone the repository with "git clone https://github.com/sacrtap/Opc_Kit" and add it to your Claude Code skills directory (see the Installation section above).

What programming language is Opc_Kit written in?

Opc_Kit is primarily written in Python. It is open-source under sacrtap on GitHub, so you can review or fork the full source.

Are there alternatives to Opc_Kit?

Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh Opc_Kit against similar tools.

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