hookradar-agent-skill 是做什么的？
将您的 AI 智能体连接到 HookRadar，通过 MCP 标准自动化竞争创意研究并分析广告表现数据。
将您的 AI 智能体连接到 HookRadar，通过 MCP 标准自动化竞争创意研究并分析广告表现数据。
该技能通过 MCP（模型上下文协议）标准，将 AI 智能体（如 Claude Code、Cursor 或 Codex）无缝连接到 HookRadar 平台。它使 AI 能够自动化执行竞争创意研究，包括广告素材分析、表现数据洞察和趋势识别。用户可以直接通过自然语言指令，触发 HookRadar 的 API 来查询广告库、对比不同素材效果、获取广告文案和视觉元素分析。这极大地减少了人工调研时间，尤其适用于数字营销团队、产品经理和增长黑客。支持多种 AI 代理环境，并基于标准协议确保安全可控的数据访问。技能的核心价值在于将竞争情报工作流嵌入到日常开发与决策中。
npx skills add Anagogic-blastinggelatin157/hookradar-agent-skillInstalled? Explore more 研究与数据分析 skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
将您的 AI 智能体连接到 HookRadar，通过 MCP 标准自动化竞争创意研究并分析广告表现数据。
USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.
Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.
Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Agent skill repository discovered by 10x-chat research.
Review backend code for quality, security, maintainability, and best practices based on established checklist rules. Use when the user requests a review, analysis, or improvement of backend files (e.g., `.py`) under the `api/` directory. Do NOT use for frontend files (e.g., `.tsx`, `.ts`, `.js`). Supports pending-change review, code snippets review, and file-focused review.