544 件 ・ 関連度順
概要と使いどころ
Diagram design reference library (14 types — architecture, flowchart, sequence, state, ER, timeline, swimlane, quadrant, nested, tree, org chart, layers, venn, pyramid). In ppt-master this is consumed by the Executor when hand-authoring diagram-type SVG pages — it is NOT a standalone HTML generator here. Read for deep per-type layout conventions.
日本語の概要は準備中です。原文の説明を表示しています。
Create original short videos using the 升级讽刺｜新物登场旧爱被移走 Creative DNA for MiniMax H3 or Seedance 2.0. Use when the user wants this causal, camera, motion, rhythm, or payoff structure with new subjects and surfaces.
日本語の概要は準備中です。原文の説明を表示しています。
Create original short videos using the 程序错位｜扫描到实物双确认 Creative DNA for MiniMax H3 or Seedance 2.0. Use when the user wants this causal, camera, motion, rhythm, or payoff structure with new subjects and surfaces.
日本語の概要は準備中です。原文の説明を表示しています。
Fix silent camera/microphone failure on Flutter macOS when using permission_handler plugin. Use when: (1) Camera screen shows placeholder but no error on macOS, (2) CameraPermissionError state is emitted but cause is unclear, (3) permission_handler checkCameraStatus() or checkMicrophoneStatus() throws exceptions on macOS desktop, (4) Camera works on iOS/Android but fails silently on macOS. The permission_handler plugin doesn't work reliably on macOS - bypass it and let macOS handle permissions at the system level.
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Use when the user has a research question and needs a complete experiment package — design document, runnable code, results (measured or simulated with honest provenance), publication-grade figures, structured report. Single-stage, no Python runtime.
日本語の概要は準備中です。原文の説明を表示しています。
Pinia v3 Vue state management with defineStore, getters, actions. Use for Vue 3 stores, Nuxt SSR, Vuex migration, or encountering store composition, hydration, testing errors.
日本語の概要は準備中です。原文の説明を表示しています。
Type-safe React forms with React Hook Form and Zod validation. Use for form schemas, field arrays, multi-step forms, or encountering validation errors, resolver issues, nested field problems.
日本語の概要は準備中です。原文の説明を表示しています。
Audits the agent rules in the current folder (AGENTS.md, nested AGENTS.md files) and the skill descriptions the agent sees at start, then reports what to cut, move or rewrite and edits only after the user says yes. Use on «аудит правил», «проверь AGENTS.md», «почему агент не слушается правил», «проверь скиллы».
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Run an honest market-fit and viability audit of any project or idea and produce a decision doc, not code. Use when someone asks "is this viable as a business", "audit the market fit", "make the case and compare to competitors", "should I apply to YC or bootstrap", or wants to validate a project, product, or market before investing more time. Gathers verifiable traction data first, researches the competitive field, gets an independent cold read, writes a doc with pre-committed pass/middle/kill criteria and a concrete week-1 assignment, then hardens it with an adversarial review loop.
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Use when the user wants to simplify, clean up, refactor, tidy, or refine code — their staged/unstaged git changes or a target file/path. Reduces complexity, flattens nesting, removes redundancy and dead code, scores each change by value (holding low-value churn), then runs tests to prove nothing broke. Invoke on: "simplify", "simplify this", "simplify my code/changes", "clean up", "clean this up", "clean up my changes", "refactor this", "make this cleaner", "tidy this up", "reduce complexity", "flatten this", "remove dead code", "make it more readable", "polish before commit", or "absolute simplify". Acts on your working diff; for repo-wide dead code use absolute-prune; for lint/type debt use absolute-debt.
日本語の概要は準備中です。原文の説明を表示しています。
Think and work like an expert Machine Learning Researcher. Use when a task calls for Machine Learning Researcher judgment. Reasons from population risk, double descent, and inductive bias; enforces sacred test sets, hierarchical ablations, nested CV, and HELM/Dynabench-aware benchmarking; reports with NeurIPS and Pineau reproducibility checklists while treating leakage, meta-overfitting, benchmark contamination, Goodhart gaming, and seed variance as first-class failure modes.
日本語の概要は準備中です。原文の説明を表示しています。
Think and work like an expert Data Scientist. Use when a task calls for Data Scientist judgment. Reasons from CRISP-DM business estimands, leakage-safe sklearn Pipelines and nested CV, SQL/warehouse semantic metrics, A/B power and SRM/AA guardrails, causal DAG covariate discipline, and Model Cards/Datasheets while treating train-test leakage, Simpson's paradox, peeking, and PSI>0.25 drift as first-class failure modes.
日本語の概要は準備中です。原文の説明を表示しています。
Think and work like an expert Community Ecologist. Use when a task calls for Community Ecologist judgment. Reasons from Vellend's four processes and Chesson stabilizing/equalizing coexistence through PERMANOVA/betadisper, betapart turnover–nestedness, Gotelli SIM9/C-score null models, and vegan/entropart/picante pipelines while treating compositional closure, dispersion heterogeneity, and pseudoreplicated quadrats as first-class failure modes.
日本語の概要は準備中です。原文の説明を表示しています。
Think and work like an expert Astrostatistician. Use when a task calls for Astrostatistician judgment. Reasons from selection functions, censored flux limits, and look-elsewhere trial factors through Cobaya/emcee/dynesty cosmology, GP-coupled exoplanet inference, Landy–Szalay clustering, photo-z σNMAD calibration, and SBI (sbi/LtU-ILI) while treating Malmquist bias, prior-driven tensions, and detrend-then-fit transit bias as first-class failure modes.
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Plan and scope production work with Odyssey's real-time interactive video world models (odyssey.ml — Odyssey-1/Odyssey-2/Starchild-1/Agora-1). Use when a request involves generating video that a user steers live with keyboard, text, speech, or controller input (streamed frames that respond in the moment), or when someone must decide between Odyssey-style interactive generation and offline clip generators (Sora/Veo/Kling) or downloadable 3D / game engines. Covers what is verified versus announced, current access routes, latency and coherence limits, feasible-now versus speculative use cases, pricing/access terms, and content/rights considerations. This is a fast-moving research-stage product; the skill teaches honest scoping, not a promise of production reliability.
日本語の概要は準備中です。原文の説明を表示しています。
Plan, produce, adapt, finish, deliver, and improve platform-ready short vertical social videos from a brief, script, transcript, or source media. Use for TikTok videos, Instagram or Facebook Reels, YouTube Shorts, LinkedIn vertical clips, and cross-platform social cutdowns when the work requires audience and objective definition, an honest hook and promise, short-form beat or shot planning, UI-safe layout, captions and accessibility, speech/music/SFX mixing, platform-specific exports, rights and AI or sponsorship disclosure, analytics-led retention iteration, or final QA and repair. Do not use as a provider-specific image, video, voice, or music generation guide.
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Build forest plots (HR, OR, RR, beta-coefficient summaries with CIs) and funnel plots (meta-analysis publication-bias diagnostics) using forestplot, metafor, ggforest, and MendelianRandomization with proper axis-scaling, summary-diamond placement, subgroup nesting, and Egger / trim-and-fill asymmetry tests. Use when summarizing effects across subgroups, trials, or instruments — meta-analysis, Mendelian randomization, subgroup HRs.
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Retrieve records from NCBI databases using Biopython Bio.Entrez (EFetch, ESummary). Use when downloading sequences, fetching GenBank/GenPept records, getting document summaries, parsing nested XML, navigating GI deprecation, choosing between rettype+retmode combinations, and parsing into Biopython SeqRecord/SwissProt objects. Covers nucleotide, protein, gene, pubmed, sra, gds, taxonomy, snp, clinvar.
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Plot per-group distributions of continuous data using boxplots, violins, beeswarms, quasirandom jitter, and raincloud plots with sample-size honesty (Weissgerber 2015), KDE-bandwidth awareness, and N-aware encoding choices. Use when comparing distributions across a small number of groups — expression per cluster, biomarker per arm, scores per condition — and the bar-of-mean default is misleading.
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Calculates species richness, diversity, and turnover using the Hill number framework with iNEXT coverage-based rarefaction/extrapolation, asymptotic diversity estimation, and beta diversity partitioning (betapart turnover vs nestedness). Compares assemblages using coverage-standardized rather than size-standardized rarefaction. Use when quantifying biodiversity from species abundance or incidence data, comparing diversity across sites, or constructing rarefaction curves. Not for clinical 16S microbiome alpha/beta diversity (see microbiome/diversity-analysis).
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End-to-end biomarker discovery workflow from expression data to validated biomarker panels. Covers feature selection with Boruta/LASSO, classifier training with nested CV, and SHAP interpretation. Use when building and validating diagnostic or prognostic biomarker signatures from omics data.
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Test payment and checkout flows end to end against PSP sandboxes — Stripe first, with the general pattern for Adyen/Braintree/PayPal. Covers Stripe test-mode card numbers and their decline codes, the 3DS/SCA challenge flow and its nested-iframe handling in Playwright, test clocks for subscription/billing-cycle simulation, webhook testing (stripe listen/trigger, signature verification, idempotency), failed/retried payments and refunds, and never using real cards. Use when: "test Stripe checkout," "payment test," "3DS test," "test webhook signature," "test subscription renewal," "test clock," "refund test," "decline card test," "checkout E2E." Not for: General API contract testing of non-payment endpoints — api-testing. PCI-DSS/regulatory compliance audit — compliance-testing. Related: api-testing, playwright-automation, compliance-testing, test-data-management, qa-project-context.
日本語の概要は準備中です。原文の説明を表示しています。
Ember.js is an opinionated JavaScript framework for large single-page web apps, built on convention over configuration: Glimmer components, tracked state, nested routing, services, Ember Data (WarpDrive) and the ember-cli build tool. Use when someone asks to "build an Ember app", "create an Ember component or route", "upgrade Ember", "use Ember Data", or "convert Ember templates to .gjs/.gts".
日本語の概要は準備中です。原文の説明を表示しています。
Makes working code easier to read and change without altering what it does, and proves the behaviour stayed the same. Use when someone says "simplify this", "clean up this function", "this file is a mess", "reduce the complexity", "refactor for readability", "tidy my diff before the PR", or when a linter reports high cyclomatic complexity or deep nesting. Covers pinning current behaviour with characterization tests, measuring complexity, choosing a named refactoring, applying it in small verified steps, and reporting suspected bugs found on the way instead of fixing them silently.
日本語の概要は準備中です。原文の説明を表示しています。