Research, academic papers, education, and exam prep (4.5K skills)
ProteoDisco is an R package to facilitate proteogenomics studies. It houses functions to create customized (variant) protein databases based on user-submitted genomic variants, splice-junctions, fusion genes and manual transcript sequences. The flexible workflow can be adopted to suit a myriad of research and experimental settings.
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A post hoc cell type classification tool to fine-tune cell type annotations generated by any cell type classification procedure with semi-supervised learning algorithm AdaSampling technique. The current version of scReClassify supports Support Vector Machine and Random Forest as a base classifier.
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Manhattan plot and QQ Plot are commonly used to visualize the end result of Genome Wide Association Study. The "ggmanh" package aims to keep the generation of these plots simple while maintaining customizability. Main functions include manhattan_plot, qqunif, and thinPoints.
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A package that provides a client interface to the Kyoto Encyclopedia of Genes and Genomes (KEGG) REST API. Only for academic use by academic users belonging to academic institutions (see <https://www.kegg.jp/kegg/rest/>). Note that KEGGREST
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Use when you want phase research without planning: to investigate before deciding a phase is feasible, or to re-research after a plan already exists. Standalone command; most workflows should use /gsd-plan-phase instead.
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Use when the current milestone has shipped and it is time to scope the next one, or when the user asks to start a new milestone. Updates PROJECT.md, then runs questioning, research, requirements, and roadmap.
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Use after a phase has been discussed, or when the user asks for a PLAN.md for a roadmap phase. Researches, spawns gsd-planner, verifies with gsd-plan-checker, and iterates; supports --gaps, --prd, --skip-research.
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Use for a trivial task the user can describe in one sentence: a typo, config change, small refactor or forgotten commit. Executes inline with no subagents and no PLAN.md; anything needing research or planning belongs to /gsd-quick.
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Use when the user wants to think through an idea before committing to a plan, e.g. /gsd-explore auth strategy. Runs a Socratic session, optionally spawns research, then routes output to notes, seeds, requirements, or new phases.
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Use when starting GSD in a repo that has no .planning/ yet, or the user wants a new project set up. Questioning, optional research, requirements, and roadmap produce .planning/PROJECT.md, REQUIREMENTS.md, ROADMAP.md, and STATE.md.
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Your education and edtech brain trust. 25 named personas across 7 cells covering learning science, curriculum design, AI tutoring, higher-ed strategy, edtech platforms, assessment, and workforce development.
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Your AI research and engineering brain trust. 59 named personas across 8 cells covering frontier labs, applied product, model architecture, reasoning/RL/agents, alignment and interpretability, theory and science of DL, multimodal and…
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Use when finished work needs to reach a coco-managed repository (coco-research/coco or similar) — verifies branch state, commits, pushes through the corporate DLP guard only when actually needed, opens a PR against main, waits for CI, and reports the result. Never merges, never pushes to main directly.
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Codex-only — use when the user asks to run claude-smart commands in Codex, including claude-smart show, learn, restart, dashboard, clear-all, or slash-like requests such as /claude-smart:learn. In Claude Code the native plugin slash commands handle these; do not invoke this skill there.
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系统化学习材料生成器。给一个新领域/技术/概念，AI 自主调研、搭体系、产出 HTML 学习材料（含骨架/案例/工程化/争议+盲区）。当用户说"我要学 X / 帮我系统拆解 X / 我想吃透 X 这个领域 / 给我整理 X 的全貌 / 深度调研 X 给我系统讲讲 / 把 X 搞透"时触发。不适用于"X 行不行/为什么 Y"（使用可用的调研工具直接研究）、"X 有哪些好玩案例"（用 case-radar 给散点）、"把这堆素材整理成 HTML"（用 readable-output 处理已有素材）、文章写作（用 writing-assistant）、整页界面方案（用 page-solution-design）。
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带用户精读一篇文章/文档并真正学透（不是出摘要）。五步：抽干货 → 切讲次 → 每讲跑「学-考-讲」循环 → 对号入座 → 实操+测验+讲错题+蒸馏。每讲产出 HTML 课件 + 笔记落盘；讲完必考一次，用户复述后必须挑不精确处拧紧；抽象概念上可交互演示（能点能跑）；全程用用户自己的业务场景当案例；学完出多题型自动判分测验卷，最后把收获蒸馏回用户的工具。核心触发条件是用户要的是"学会"而不是"要一份结果"，例如"我们一起学这篇文章/这个链接"、"带我学"、"精读"、"我想学会 X"、"这篇我看不懂你给我讲讲"。有具体材料（链接、本地文件、PDF，或用户自己的 skill/文档/代码）时直接开跑；只有学习意图而没材料时仍走本 skill，但开工第一件事是和用户一起把材料定下来，禁止凭记忆开讲。不适用于：只要一份总结/摘要/教程长文，用户读完就完、不需要答题（用 readable-output）、只是搜集资料做调研（使用可用的网页/平台取材工具）、帮我写 PRD/测试用例（用 prd-test-writer）、以及用户其实是想让你直接把活干了（那就直接做）。
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Build prospect lists where the prospect is already one hop from the client, and write the line that says so. Seven members, each with its own source. Current-customer alumni is the priority member - everyone who ever worked at one of the client's customers or case-study companies and has since moved on. Triggers on "warm intro", "who do we know at that account", "they used to work at our customer", "alumni of our case study company", "shared investor angle", "who is in the same city as our rep", "did they visit our site". Outputs warm_intro_line plus a per-member evidence column.
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Turns one customer case study into the tightest list of companies that would read that case study and see themselves. Decomposes WHY the case-study company resonates into concrete attributes, translates those attributes into database filters, intersects them with a lookalike anchor, then widens with a model judge. Triggers on "find more companies like our best customer", "who would our case study land with", "lookalikes of X", "build a list around this case study", "companies like our happiest client", "expand this list, it is too small". Outputs a filter set plus one merge field naming which case study to cite.
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Finds a prospect company's own case-study or customer-stories page and pulls one named customer off it, so email 1 can open with "saw your work with Intercom". Triggers on "case study", "customer stories", "who are their clients", "saw your work with X", "name-drop one of their customers", "logos on their site". Outputs case_study_line, a short clause that finishes the sentence "Saw ...".
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Autonomous cold email campaign launcher. Takes one target company domain, scrapes their website, generates an ICP with Claude, pulls matching leads via Prospeo, enriches emails + company descriptions, personalizes each lead with parallel Claude Code Task sub-agents (A/B/C variants), and uploads as a live Smartlead campaign. Uses local JSON files for state (no database required). Use for automated daily campaign launches after you have an initial `client-profile.yaml` from /icp-onboarding. Triggers on "auto-research", "launch an automated campaign", "daily campaign", "run the research loop".
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Weekly. Scores the week from the ledgers with a source path beside every number and never writes a number it did not count in a file this run. It names exactly two things and files both as cards, the one fix worth doing next week and the one thing to stop, and it replays every learned browser flow once, read only, so a drifted selector is found on a Friday rather than on a Tuesday morning a routine needed it.
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Runs once by hand on the first day and once a month after that. On the first run it researches the business from its own public surfaces, reads the member's own already published posts, and builds the voice file from real samples rather than from an idea of a voice, then writes the plan, creates the proof inventory, seeds the opening slots, and registers the recurring jobs. On every monthly run it re reads the evidence the kit produced and rebuilds only what the evidence contradicts. It publishes only where you released the channel, never replies, spends only where you released it, and it never enters a credential.
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Weekdays, browser only when the card needs one. Takes the next ready cards off the launch board and does the work each one names: stages copy into the dashboard, fills a directory or press form and leaves it open in its tab, verifies a setup, packages a handoff, or researches its own next targets. It ticks its own card the moment it has verified the file that closes it. It submits only where you released the channel, sends only where you released the channel, spends only where you released it, and never touches a credential.
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Runs once by hand on the first day and once a month after that, light browser lane. On the first run it researches the business from its own published surfaces before asking anything, writes the strategy folder, creates the ledgers, seeds the opening cards, builds the single page dashboard, reconciles the schedule table, and registers the eight recurring jobs. On every monthly run it re-reads a month of the kit's own evidence, applies what changed, adds a tab for a channel that gained volume, rebuilds, and reconciles every registered job against the table. It holds every outbound action unless you released the channel, and it never enters a credential.
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