paper-context-resolver 是做什麼的？
Rigor Paper Context 輔助工具，用於 README-first 深度學習儲存庫再現。僅在 README 和儲存庫檔案留下狹窄的再現關鍵缺口，且任務是從主要論文來源解析特定論文細節（如資料集分割、預處理、評估協議、檢查點映射或執行時假設）並記錄衝突時使用。請勿用於一般論文摘要、儲存庫掃描、環境設置、命令執行、僅標題論文查詢，或預設取代 README 指引。
Rigor Paper Context 輔助工具，用於 README-first 深度學習儲存庫再現。僅在 README 和儲存庫檔案留下狹窄的再現關鍵缺口，且任務是從主要論文來源解析特定論文細節（如資料集分割、預處理、評估協議、檢查點映射或執行時假設）並記錄衝突時使用。請勿用於一般論文摘要、儲存庫掃描、環境設置、命令執行、僅標題論文查詢，或預設取代 README 指引。
這是一個專為深度學習論文再現場景設計的技能，名稱維持為「llllllama/paper-context-resolver」。其核心功能是作為 Rigor Paper Context 輔助工具，在 README 優先的再現流程中，當 README 與儲存庫檔案遺留了狹窄但關鍵的再現缺口時，從主要論文來源精準解析特定論文細節，例如資料集分割方式、預處理步驟、評估協議、檢查點對應關係或執行時假設，並記錄可能存在的衝突。此技能適用於 Claude Code、Cursor 或 Codex 等 AI 代理平台，透過讀取論文全文來填補這些再現所需的具體資訊。它不應用於一般論文摘要、儲存庫掃描、環境設置、命令執行或僅以標題查詢論文，也預設不應取代 README 中的指引。操作方式基於用戶提供的任務描述與相關檔案路徑，技能會主動從論文文本中提取並提供精確的上下文資訊，確保再現過程的準確性。
npx skills add https://github.com/lllllllama/ai-paper-reproduction-skill/tree/main/skills/paper-context-resolverInstalled? 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 →
Rigor Paper Context 輔助工具，用於 README-first 深度學習儲存庫再現。僅在 README 和儲存庫檔案留下狹窄的再現關鍵缺口，且任務是從主要論文來源解析特定論文細節（如資料集分割、預處理、評估協議、檢查點映射或執行時假設）並記錄衝突時使用。請勿用於一般論文摘要、儲存庫掃描、環境設置、命令執行、僅標題論文查詢，或預設取代 README 指引。
This repo contains 4 individual skills — each has its own dedicated page.
Main orchestrator for README-first AI repo reproduction. Use when the user wants an end-to-end, minimal-trustworthy reproduction flow that reads the repository first, selects the smallest documented inference or evaluation target, coordinates intake, setup, trusted execution, optional trusted training, optional repository analysis, and optional paper-gap resolution, enforces conservative patch rules, records evidence assumptions deviations and human decision points, and writes the standardized `repro_outputs/` bundle. Do not use for paper summary, generic environment setup, isolated repo scanning, standalone command execution, silent protocol changes, or broad research assistance outside repository-grounded reproduction.
Rigor Setup skill for README-first deep learning repo reproduction. Use when the task is specifically to prepare a conservative conda-first environment, checkpoint and dataset path assumptions, cache location hints, and setup notes before any run on a README-documented repository. Do not use for repo scanning, full orchestration, paper interpretation, final run reporting, or generic environment setup that is not tied to a specific reproduction target.
RigorPilot trusted execution and reporting skill for README-first deep learning repo reproduction. Use when the task is specifically to capture or normalize evidence from the selected smoke test or documented inference or evaluation command and write standardized `repro_outputs/` files, including patch notes when repository files changed. Do not use for training execution, initial repo intake, generic environment setup, paper lookup, target selection, hidden scientific-meaning changes, or end-to-end orchestration by itself.
Rigor Intake helper for README-first deep learning repo reproduction. Use when the task is specifically to scan a repository, read the README and common project files, extract documented commands, classify inference, evaluation, and training candidates, and return the smallest trustworthy reproduction plan to the main orchestrator. Do not use for environment setup, asset download, command execution, final reporting, paper lookup, or end-to-end orchestration.
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.