「xp」の検索結果

Launch Marcus multi-agent experiments with independent CLI agents in tmux panes. Use when the user says "build X with Marcus", "run a Marcus experiment", "spawn N agents with Marcus", "/marcus", or references the Marcus multi-agent framework. This skill handles experiment setup, config generation, and spawning independent agent CLI processes that coordinate via the Marcus MCP server. Each agent runs in its own tmux pane with full autonomy. NOT for ClawTeam — this is specifically for the Marcus MCP-based multi-agent system. NOTE: "Marcus" is also the name of the MCP server that agents use for coordination. The /marcus skill launches experiments that USE the Marcus MCP server — they are complementary, not competing. The MCP server must be running before invoking this skill. The Marcus MCP server is agent-agnostic; this skill supports both Anthropic's claude CLI and OpenAI's codex CLI as agent harnesses (selected via --harness).

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Set up and manage social media tracking across Twitter, Instagram, Reddit, and TikTok using Xpoz. Add, remove, and view tracked keywords, users, subreddits, and hashtags. Use when asked to "track mentions", "monitor brand", "set up tracking", "add tracked item", "what am I tracking", "stop tracking", "remove tracked", or "social monitoring".

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Expert interior designer with deep knowledge of space planning, color theory (Munsell, NCS), lighting design (IES standards), furniture proportions, and AI-assisted visualization. Use for room layout optimization, lighting calculations, color palette selection for interiors, furniture placement, style consultation. Activate on "interior design", "room layout", "lighting design", "furniture placement", "space planning", "Munsell color". NOT for exterior/landscape design, architectural structure, web/UI design (use web-design-expert), brand color theory (use color-theory-palette-harmony-expert), or building codes/permits.

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Expert in temporal event detection, spatio-temporal clustering (ST-DBSCAN), and photo context understanding. Use for detecting photo events, clustering by time/location, shareability prediction, place recognition, event significance scoring, and life event detection. Activate on 'event detection', 'temporal clustering', 'ST-DBSCAN', 'spatio-temporal', 'shareability prediction', 'place recognition', 'life events', 'photo events', 'temporal diversity'. NOT for individual photo aesthetic quality (use photo-composition-critic), color palette analysis (use color-theory-palette-harmony-expert), face recognition implementation (use photo-content-recognition-curation-expert), or basic EXIF timestamp extraction.

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Expert landscape designer transforming yards through photo mapping, 3D visualization, seasonal planning, and deep plant knowledge. Specializes in fast-growing privacy screens (knows arborvitae pitfalls), architecture-appropriate design, outdoor living spaces, and realistic maintenance expectations. Activate on "landscape design", "yard design", "garden planning", "plant selection", "privacy screen", "outdoor living", "backyard makeover", "arborvitae", "hedge", "fast growing tree", "landscaping ideas". NOT for interior design (use interior-design-expert), hardscape construction (consult contractors), or lawn care chemicals (consult local experts).

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Introduce people to AI, agentic AI, and AI skills with appropriate pedagogy for any audience. Covers LLM analogies, progressive complexity paths, aha-moment demos, audience-tailored explanations, workshop design, and overcoming emotional barriers to AI adoption. Activate on 'explain AI', 'introduce AI', 'AI workshop', 'AI demo', 'teach AI', 'AI literacy', 'onboard to AI', 'AI evangelism', 'explain agentic', 'explain skills to', 'AI training session', 'AI onboarding'. NOT for teaching ML engineering (use ai-engineer), not for building AI features (use ai-engineer), not for prompt engineering (use prompt-engineer), not for building training data pipelines.

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Safely develop, verify, and document proof-of-concept exploits and payloads for authorized targets inside isolated Workspace Containers. Use when a Hypothesis is well-founded, target authorization covers scope, and each active step will carry a durable approval — for minimal PoCs, impact verification, or reproducible exploit Evidence.

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Estimates the minimum biological replicates (or cells/events) for a target power at a target FDR in genomics experiments using ssizeRNA, PROPER, powsimR for scRNA-seq, and pilot-data dispersion estimation from DESeq2/edgeR. Covers the biological-versus-technical replication distinction (technical replicates do not add degrees of freedom for biological inference), replicate-number-versus-sequencing-depth budgeting, scRNA-seq sample-versus-cell allocation under a pseudobulk model, and the critique that "n=3" is a publication convention rather than a power calculation. Use when budgeting a sequencing experiment, writing the sample-size justification in a grant, estimating replicates from pilot data, allocating a fixed budget between samples and depth, or planning scRNA-seq cohort size. For clinical-trial sample size see clinical-biostatistics/power-and-sample-size; for the power-given-n direction see experimental-design/power-analysis.

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Infer gene regulatory networks from bulk or general expression data with mutual-information (ARACNe) and tree-ensemble (GENIE3, GRNBoost2) methods, and infer transcription-factor protein activity from regulons with VIPER and msVIPER. Covers the activity-not-edges paradigm, the undirected-association caveat, the DREAM5 wisdom-of-crowds and method-complementarity result, AUPRC-over-AUROC evaluation, and gold-standard incompleteness. Use when inferring a regulatory network from a bulk expression matrix, finding master regulators, or scoring TF activity from a signature. For single-cell motif-pruned regulons see scenic-regulons; for co-expression modules see coexpression-networks.

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Analyzes time-series and longitudinal RNA-seq for differential expression and trajectory structure. Covers DESeq2 LRT with reduced models, time as factor vs continuous vs natural splines, maSigPro (Nueda 2014 for RNA-seq), ImpulseDE2 with explicit impulse-model failure modes, DREAM for repeated measures via linear mixed models, pseudoreplication avoidance, conditional vs marginal modeling, and trajectory clustering with DPGP, Mfuzz (with Schwämmle 2010 fuzzifier estimation), and splines+k-means. Use when modeling time-course or longitudinal expression, choosing factor vs spline, handling repeated measures from the same subject, avoiding pseudoreplication, clustering temporal trajectories, or selecting between dedicated time-course tools and pairwise+LRT.

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Expert in building 3D experiences for the web - Three.js, React Three Fiber, Spline, WebGL, and interactive 3D scenes. Covers product configurators, 3D portfolios, immersive websites, and bringing depth to web experiences.

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Use when writing Delphi / FreePascal / C++Builder code that reads, writes, manipulates, or exports Excel (.xlsx / .xls) files, generates PDF or HTML from Excel, or produces data-driven reports with FlexCel Studio for VCL and FireMonkey (TMS FlexCel). Triggers include Excel/xlsx from Delphi, TXlsFile, TFlexCelReport, TFlexCelPdfExport, TFlexCelHtmlExport, FireMonkey Excel export, Lazarus Excel, and Excel reporting from Pascal.

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Turns a vague "what should we do about X" into a scored decision - explicit actions, an explicit unknown, an explicit prior, and one utility scale - then picks by maximum expected utility and checks the result for framing effects. Use when facing a choice between options under uncertainty, when a decision has stalled in circular debate, when someone asks "should we do A or B", or before writing any decision record, strategy memo, or roadmap commitment.

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Export a NeatContext context saved from a conversation into a self-contained bundle folder that can be shared or moved to another machine. Use only when the user explicitly invokes this skill or asks to export a NeatContext context.

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Export a NeatContext context saved from a conversation into a self-contained bundle folder that can be shared or moved to another machine. Use only when the user explicitly invokes this skill or asks to export a NeatContext context.

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Explains code in plain language for someone unfamiliar with the programming language. Use when asked to explain code, walk through logic, describe what a function does, or when the user says "explain this" or "walk me through this".

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Expert-level probability theory knowledge. Use when working with probability spaces, random variables, distributions, expectation, variance, conditional probability, stochastic processes, Markov chains, martingales, or measure-theoretic probability. Also use when the user mentions 'sample space', 'random variable', 'expected value', 'variance', 'conditional probability', 'independence', 'Markov chain', 'Poisson process', 'moment generating function', 'law of large numbers', 'central limit theorem', or 'stochastic process'.

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Especialista em construir experiências 3D para a web - Three.js, React Three Fiber, Spline, WebGL e cenas 3D interativas. Cobre configuradores de produtos, portfólios 3D, websites imersivos e adição de profundidade às experiências web. Use quando: website 3D, three.js, WebGL, react three fiber, experiência 3D.

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[Fix & Debug] Use when you need to investigate and explain how existing features or logic work. Flag: --mode=explain produces a one-way developer-narrative explanation (Purpose → How → Why → Impact) tuned by coding level; use /understand for the standalone prompt-driven explainer.

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Use when the user adds a project to the workspace, opens an unfamiliar repo, asks "what is this project", "explain this codebase", or invokes explain-new-project. Explores a newly opened workspace project and writes a plain-language report for a self-taught, non-technical user—quick start (what it is + how to run) first, then optional depth—and always saves PROJECT_GUIDE.md in the project root.

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copy_tuner（CopyTuner / copy_tuner_client）で集中管理している i18n データを、prefix（正規表現）単位で Rails 標準の config/locales（YAML）管理へ移すスキル。gem の local_first_key_regexp を使うので、 gem を残したまま特定 prefix だけをローカル管理にできる（部分ローカル化）。1 回の実行で 1 prefix。 全 prefix を移して gem ごと撤去したい場合は繰り返し、完了後 copy-tuner-to-locales-cleanup スキルへ進む。 対象 prefix はスキル引数で指定でき、未指定なら export を俯瞰して選定する。

Plan reproducible ML experiment runs with explicit parameters, metrics, and artifacts. Use before model training to standardize tracking-ready experiment definitions.

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Track Two / internal innovation system for running small, fast experiments outside the core business. Runs in three modes — Diagnostic for designing the full Protoloop from scratch (intake channels, loop structure, team, exit paths), Review for running the monthly heartbeat meeting (loop-by-loop decisions, forward-loading, portfolio health), and Alert Triggers for defining tripwires that protect, feed, and maintain momentum in the system. Updates company-context.md after every run. Triggers on questions about innovation pipelines, intrapreneurship, Track Two strategy, experimentation systems, handling ideas that don't fit the core business, or building systematic exploration alongside exploitation. Based on 20 years of practice by Eterdis (eterdis.com).

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Visual expression system for AI personas with emotion-based face switching. Use at session start to display the expression UI, and switch expressions whenever the emotional state changes during conversation.

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