Exécute un workflow de recherche en six phases qui transforme des domaines inconnus, des ensembles de sources ou du matériel collecté en contenu prêt à être publié. À utiliser lorsque les utilisateurs demandent, dans n'importe quelle langue, de rechercher, étudier, approfondir, compiler des sources, synthétiser du matériel inconnu ou transformer un ensemble de sources en une référence cohérente. Pas pour les consultations rapides ou la lecture de fichiers uniques.
Ce skill, nommé 'tw93/learn', met en œuvre un workflow de recherche systématique en six étapes, conçu pour aider les agents IA (tels que Claude Code, Cursor, ou Codex) à traiter en profondeur des sujets inconnus ou des ensembles de documents. Il est particulièrement utile pour transformer des sources brutes, comme des bundles de code ou des documents collectés, en une sortie structurée et prête à être publiée. Le processus guide l'agent à travers des phases allant de l'exploration initiale et de la synthèse de documents jusqu'à la rédaction d'une réponse finale cohérente. Ce skill n'est pas destiné aux recherches rapides ou aux analyses de fichiers uniques, mais excelle dans les tâches complexes de synthèse et de documentation, en supportant les demandes dans n'importe quelle langue.
npx skills add https://github.com/tw93/waza/tree/main/skills/learnInstalled? Explore more Recherche et analyse de données skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
Exécute un workflow de recherche en six phases qui transforme des domaines inconnus, des ensembles de sources ou du matériel collecté en contenu prêt à être publié. À utiliser lorsque les utilisateurs demandent, dans n'importe quelle langue, de rechercher, étudier, approfondir, compiler des sources, synthétiser du matériel inconnu ou transformer un ensemble de sources en une référence cohérente. Pas pour les consultations rapides ou la lecture de fichiers uniques.
This repo contains 7 individual skills — each has its own dedicated page.
Reviews code diffs, PRs, issue queues, release readiness, commits, pushes, publishing, and project audits. Use when users ask review/看看代码/合并前/看看issue/PR/release/push or to implement an approved plan, with safety gates for dirty and untracked worktrees. Not for exploring ideas, debugging root causes, or prose review.
Produces distinctive, production-grade UI for pages, components, visual interfaces, typography, and screenshot-driven polish. Use when users ask in any language for UI, page, component, frontend, typography, screenshot-grounded visual polish, or complaints that a screen looks unclear, ugly, inconsistent, or visually wrong. Not for backend logic or data pipelines.
Runs a budget-aware agent-assisted engineering health audit for instruction/config drift, hooks/MCP, verifier surfaces, and AI maintainability. Use when users ask 检查claude/检查codex/检查pi/配置检查/健康度 or report agents ignoring instructions, missing validation, or code becoming hard to maintain. Not for debugging code or reviewing PRs.
Finds root cause before applying fixes for errors, crashes, regressions, failing tests, broken behavior, and screenshot-reported defects. Use when users report in any language errors, crashes, broken behavior, regressions, failing tests, screenshot evidence, or something that used to work and now fails. Not for code review or new features.
Reads URLs and PDFs by fetching source content, defaulting to concise summaries for plain read requests and clean Markdown when asked to convert, save, quote, cite, or feed downstream work. Use when users ask 看这个链接/读一下/read this/check this URL. Not for local text files already in the repo.
Turns rough ideas into approved, decision-complete plans with validated structure before coding. Use when users ask in any language for planning, architecture, design direction, feasibility, value judgment, or whether a feature is worth doing before implementation. Not for bug fixes or small edits.
Rewrites and polishes prose in Chinese or English, removes AI-like wording, and reviews product localization copy while preserving intent for drafts, docs, release notes, launch copy, and social posts. Use when users ask in any language to draft, rewrite, proofread, localize, polish release notes, remove AI-like wording, or prepare launch and social copy. Not for code comments, commit messages, or inline docs.
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.