Adversarial implementation review based on Block's g3 dialectical autocoding research. Use when validating implementation completeness against requirements with fresh objectivity.
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Select your agent
Option 1: Install via CLI (recommended)
Recommended (no pre-install needed)
npx clawhub@latest --dir ~/.claude/skills install adversarial-coachOr via clawhub CLI (if already installed)
clawhub --dir ~/.claude/skills install adversarial-coachβ οΈ Requires Node.js 18+. No Node? Use Option 2 below to download the ZIP instead. Install Node.js β
Option 2: Manual install (no Node required)
Download the ZIP, extract it, and place the folder at the path below. Restart your agent to activate.
Install path
~/.claude/skills/adversarial-coach/π‘Extract and place the folder at the path above, then restart your agent.
Category
πProduct ManagerPlatforms
What adversarial-coach can do for your AI workflow
Adversarial implementation directly from your Claude conversation
Works across Claude, Cursor, OpenClaw β install once, use everywhere
Trusted by 1,660+ developers worldwide
One-command installation β no complex setup required
Combine with other skills to build powerful multi-step AI workflows
Try these prompts with your AI agent after installing adversarial-coach
Help me get started with adversarial-coach
Explains what adversarial-coach does, walks through the setup, and runs a quick demo based on your current project
Use adversarial-coach to adversarial implementation review based on Block's g3 dialectical a...
Invokes adversarial-coach with the right parameters and returns the result directly in the conversation
What can I do with adversarial-coach in my product manager workflow?
Lists the top use cases for adversarial-coach, with example commands for each scenario
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adversarial-coach extends your AI assistant with the ability to adversarial implementation review based on Block's g3 dialectical autocoding research. Use when validating implementation completeness against requirements with fresh objectivity. Rather than leaving your conversation to handle this manually, you can ask your Claude agent directly β and it will take care of the task end-to-end, using adversarial-coach as its underlying capability.
adversarial-coach works across Claude, Cursor, OpenClaw through the Model Context Protocol (MCP) β an open standard that lets AI clients share tools and skills without lock-in. Because MCP is platform-agnostic by design, you install adversarial-coach once and it becomes available across all your AI clients. Whether you're working in Claude for focused sessions or Cursor for integrated workflows, the skill behaves consistently.
adversarial-coach installs like any other MCP skill: drop the folder into `~/.claude/skills/adversarial-coach/` for global access, or `.claude/skills/adversarial-coach/` to keep it scoped to one project. After a quick restart of Claude, you can trigger it explicitly with `/adversarial-coach`, or let the AI decide when it's the right tool for your request.
adversarial-coach has been installed 1,660 times, making it one of the more actively used skills in the Product Manager category. The install rate suggests it solves a real, recurring need rather than a niche edge case. The source code is open on GitHub β you can inspect it, contribute fixes, or fork it to adapt the skill for your specific setup. Like all skills on DiscoverAISkills, it is free to install and use. The broader AI skills ecosystem continues to expand as developers contribute new capabilities across categories like developer tools, data analysis, writing, automation, and more.
Place the skill folder at ~/.claude/skills/adversarial-coach/ for personal use (all projects), or .claude/skills/adversarial-coach/ for project-specific use. Restart your AI client, then invoke with /adversarial-coach or let the AI discover it automatically.
adversarial-coach supports Claude, Cursor, OpenClaw. It integrates seamlessly with these AI platforms to extend their capabilities.
adversarial-coach is free to install. Check the repository for licensing information.
Adversarial implementation review based on Block's g3 dialectical autocoding research. Use when validating implementation completeness against requirements with fresh objectivity.
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Coach
Links
Automate my product manager tasks using adversarial-coach
Identifies repetitive steps in your workflow and sets up adversarial-coach to handle them automatically
adversarial-coach is categorized under Product Manager. These skills help AI agents perform specialized tasks in this domain.
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