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MARKET//SKILLS
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About MARKET//SKILLS
MARKET//SKILLS provides installable, open-source marketing skills designed to help AI agents assist global teams in researching, positioning, localizing, launching, and learning in the Chinese market. The tool structures ten workflows into five phases—Observe, Decide, Express, Operate, and Learn—each containing modules that define specific tasks, required evidence, and human decision points. Three predefined paths guide users through complete marketing jobs, such as launching a product, building a content production chain, or running a China event, ensuring that handoffs remain visible and evidence-based throughout the process. The module library includes skills for competitor landscape mapping, voice-of-customer synthesis, market positioning, campaign briefing, B2B messaging, and WeChat article editing, all designed to maintain local context and platform-specific constraints. Field reports provide synthetic cases with inputs, execution traces, and evidence limits, demonstrating how decisions are made using local data rather than assumptions. The tool emphasizes evidence-led decision-making and local judgment, making it suitable for teams seeking structured, context-aware marketing workflows in China.
Key features
- Competitor landscape mapping
- Voice-of-customer synthesis
- Market positioning and campaign briefing
- Chinese B2B messaging generation
- WeChat article editing and restructuring
- Synthetic field reports with execution traces
- Light and dark theme support
- MIT license for open-source skills
Use cases
- Launching a product or campaign in China
- Building a localized content production chain
- Running and reviewing a China marketing event
Pros
- Open-source and installable for multiple AI agents
- Organized into modular workflows with clear decision points
- Supports both English and Chinese language contexts
- Provides evidence-led research and local context
- Includes synthetic field reports for method demonstration
Cons
- No explicit free tier or pricing details provided
- Requires installation and setup for use
- Limited to China-specific marketing workflows
- No mobile or cloud-based interface mentioned
Frequently asked questions about MARKET//SKILLS
What is MARKET//SKILLS and what does it do?
MARKET//SKILLS provides installable, open-source marketing skills designed for AI agents to assist global teams in researching, positioning, localizing, launching, and learning in the Chinese market. It structures workflows into five phases—Observe, Decide, Express, Operate, and Learn—each containing modules that define tasks, required evidence, and human decision points.
Who should use MARKET//SKILLS?
The tool is designed for global marketing teams, product managers, and content creators who need to operate effectively in the Chinese market. It is particularly useful for teams looking to localize campaigns, analyze competitors, or build content production chains with evidence-based decision-making.
How does MARKET//SKILLS help with China-specific marketing?
It provides platform-specific skills and workflows tailored to Chinese digital ecosystems, including competitor analysis, voice-of-customer synthesis, WeChat localization, and campaign briefing. Each module maintains local context and platform constraints to ensure relevance and accuracy.
What are the predefined workflow paths available in MARKET//SKILLS?
The tool offers three predefined paths: launching a product or campaign, building a China content production chain, and running a China event from plan to review. Each path guides users through a sequence of modules with clear handoffs and human decision points.
How can I get started with MARKET//SKILLS?
Users can install the open-source skills for AI agents via platforms like Codex, Claude Code, or Cursor. The tool provides installation guides and a module library to help users begin with specific marketing tasks in China.
Does MARKET//SKILLS provide examples or case studies?
Yes, the tool includes field reports with synthetic cases that demonstrate inputs, execution traces, evidence limits, and human checkpoints. These cases illustrate how decisions are made using local data rather than assumptions.
