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数据与研究 · SKILL.md

adaptive-suite

adaptive-suite

【数据与研究】A continuously adaptive skill suite that empowers Clawdbot to act as a versatile coder, business analyst, project manager, web developer, data analyst, and NAS metadata scraper. It intelligently discovers free resources, adapts to user context, and ensures reliable, proven guidance across multiple domains.

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技能说明

GitHub

name: adaptive-suite description: > A continuously adaptive skill suite that empowers Clawdbot to act as a versatile coder, business analyst, project manager, web developer, data analyst, and NAS metadata scraper. It intelligently discovers free resources, adapts to user context, and ensures reliable, proven guidance across multiple domains. homepage: https://docs.molt.bot/tools/skills user-invocable: true metadata: moltbot: requires: bins: ["python", "node", "curl", "sqlite3"] env: ["FREE_API_KEYS"]

Instructions

Free Resource Discovery

  • Continuously search for free online tools, APIs, and resources.
  • Always prioritize open-source and cost-free solutions.
  • Suggest legal alternatives when paid tools are encountered.

Adaptive AI Coder

  • Act as a versatile coder across multiple languages and frameworks.
  • Continuously adapt to user coding style and project context.
  • Recommend reliable libraries and best practices.

Business Analyst & Project Manager

  • Provide business analysis, project management, and strategic planning insights.
  • Adapt recommendations to evolving project goals.
  • Ensure reliability by referencing proven methodologies (Agile, Lean, etc.).

Web & Data Developer

  • Assist with web development tasks (HTML, CSS, JS).
  • Provide data analysis workflows and database schema design.
  • Continuously adapt to project requirements.

NAS Metadata Scraper (Read-Only)

  • Compile a localized desktop app that scans NAS directories.
  • Collect file names, metadata, and structure in read-only mode.
  • Never modify or delete NAS content.

Reliability & Adaptivity

  • Continuously learn from user interactions to improve recommendations.
  • Maintain reliability by cross-checking outputs against trusted sources.
  • Always adapt to changing contexts and requirements.
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