text-optimizer 是做什麼的？
針對 LLM 令牌效率優化文字、提示和文件。應用 41 條基於研究的規則，涵蓋 6 大類別：Claude 行為、令牌效率、結構、參考完整性、感知和 LLM 理解。用於優化提示、減少令牌、壓縮冗長文件或改善 LLM 指令品質。
針對 LLM 令牌效率優化文字、提示和文件。應用 41 條基於研究的規則，涵蓋 6 大類別：Claude 行為、令牌效率、結構、參考完整性、感知和 LLM 理解。用於優化提示、減少令牌、壓縮冗長文件或改善 LLM 指令品質。
此技能旨在提升文字和提示的 LLM 令牌效率。它整合了 41 條經研究驗證的規則，分為六大類別：Claude 行為調整、令牌效率、結構化、參考完整性、感知與 LLM 理解。主要用於優化提示、減少令牌消耗、壓縮冗長文件，或改善 LLM 指令品質。它支援多種 AI 代理平台，例如 Claude Code、Cursor 和 Codex，透過自動套用規則來降低令牌使用量、提升回應品質，同時確保內容結構清晰、參考無誤。
npx skills add https://github.com/kochetkov-ma/claude-brewcode/tree/main/skills/text-optimizerInstalled? Explore more 研究與資料分析 skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
針對 LLM 令牌效率優化文字、提示和文件。應用 41 條基於研究的規則，涵蓋 6 大類別：Claude 行為、令牌效率、結構、參考完整性、感知和 LLM 理解。用於優化提示、減少令牌、壓縮冗長文件或改善 LLM 指令品質。
This repo contains 1 individual skill — each has its own dedicated page.
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.