A Codex Skill for automatically researching, verifying, deduplicating, and generating actionable daily foreign-trade intelligence reports.
The NextBeforeAnd/daily-trade-radar skill is designed for Codex (or compatible AI agents) to automate the creation of daily foreign-trade intelligence reports. It streamlines the entire workflow by first conducting multi-source research to gather the latest trade news, policy changes, and market trends. The skill then verifies the credibility of each piece of information, deduplicates overlapping content to avoid redundancy, and finally compiles the data into a structured, actionable daily report. This skill is particularly useful for exporters, importers, and trade analysts who need to stay informed without manual effort. It supports integration with various data sources and outputs clean markdown reports. By offloading the intelligence gathering and report generation to an AI agent, users can save hours of research time and focus on strategic decision-making based on verified and unique insights.
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A Codex Skill for automatically researching, verifying, deduplicating, and generating actionable daily foreign-trade intelligence reports. This skill automates the collection and verification of foreign trade information, producing a concise daily intelligence bulletin.
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.