「pir」の検索結果

Picks the right Netlify protection layer for a deployed site and disambiguates the three unrelated things people call "auth". Use when a developer wants to password-protect a site or previews, restrict a project to their team, make a project public/private, set team visibility defaults, require SSO to view a site, or debug SSO-session symptoms like being logged out mid-session / getting 401s on an SSO-protected site / token expiry or refresh. Routes app-user login ("who is this user in my app") to the netlify-identity skill and dashboard/team SSO SSO elsewhere; this skill only chooses the perimeter layer for site/preview access.

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Production-ready patterns for building LLM applications, inspired by [Dify](https://github.com/langgenius/dify) and industry best practices.

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。

Draw from architecture, fashion, music, food, and industrial design to expand your design taste range. Use when seeking inspiration beyond digital, building diverse reference sets, or expanding creative vocabulary.

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Pull design principles from architecture, fashion, film, industrial design, and physical spaces into screen-based design. Use when seeking inspiration beyond digital, expanding creative range, or building cross-disciplinary design vocabulary.

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。

Tag design references by principle, not aesthetic. Build a library you can actually search. Use when saving references, organizing inspiration, or building a design library that returns useful results.

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。

Production-ready patterns for building LLM applications, inspired by [Dify](https://github.com/langgenius/dify) and industry best practices.

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。

Patterns for automating GitHub workflows with AI assistance, inspired by [Gemini CLI](https://github.com/google-gemini/gemini-cli) and modern DevOps practices.

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。

Schedule and execute background work on iOS using BGTaskScheduler. Use when registering BGAppRefreshTask for short background fetches, BGProcessingTask for long-running maintenance, BGContinuedProcessingTask (iOS 26+) for foreground-started work that continues in background, background URLSession downloads, or background push notifications. Covers Info.plist configuration, expiration handling, task completion, and debugging with simulated launches.

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陰謀論のハームリダクションのための科学的に正しい反転パロディを書くときに使用する。

agent 向けテキスト指示（skill / slash command / task プロンプト / CLAUDE.md 節 / コード生成プロンプト）を、バイアスを排した実行者に動かしてもらい、両面（実行者の自己申告 + 指示側メトリクス）で評価して反復改善する手法。改善が頭打ちになるまで回す。プロンプトや skill を新規作成・大幅改訂した直後、またはエージェントの挙動が期待通りにならない原因を指示側の曖昧さに求めたいときに使う。

When the user wants to create or optimize in-app paywalls, upgrade screens, upsell modals, or feature gates. Also use when the user mentions "paywall," "upgrade screen," "upgrade modal," "upsell," "feature gate," "convert free to paid," "freemium conversion," "trial expiration screen," "limit reached screen," "plan upgrade prompt," or "in-app pricing." Distinct from public pricing pages (see page-cro) — this skill focuses on in-product upgrade moments where the user has already experienced value.

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。

When the user needs marketing ideas, inspiration, or strategies for their SaaS or software product. Also use when the user asks for 'marketing ideas,' 'growth ideas,' 'how to market,' 'marketing strategies,' 'marketing tactics,' 'ways to promote,' or 'ideas to grow.' This skill provides 140 proven marketing approaches organized by category.

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。

Fast, modern JavaScript/TypeScript development with the Bun runtime, inspired by [oven-sh/bun](https://github.com/oven-sh/bun).

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。

Design patterns for building autonomous coding agents, inspired by [Cline](https://github.com/cline/cline) and [OpenAI Codex](https://github.com/openai/codex).

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。

Build a vulnerability exception and risk acceptance tracking system with approval workflows, compensating controls documentation, and expiration management.

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。

Extracts and analyzes competitors' ads from ad libraries (Facebook, LinkedIn, etc.) to understand what messaging, problems, and creative approaches are working. Helps inspire and improve your own ad campaigns.

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Prepares statistical reports for clinical trials following CONSORT 2025, SPIRIT 2025, ICH E9(R1) estimands, and FDA 2023 covariate adjustment guidance. Covers Table 1 generation, analysis populations (ITT/FAS/PP/Safety), the 5 ICH E9(R1) intercurrent-event strategies, MMRM under MAR (mmrm), reference-based MI (rbmi J2R/CR/CIR), Permutt tipping-point sensitivity, and Rubin's-rules vs frequentist variance debate. Use when preparing regulatory submissions, defining estimands, or implementing missing-data sensitivity analyses.

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。

Discover conserved quantities and symmetries from trajectory data. Identifies energy, momentum, angular momentum, and custom invariants using neural networks and symbolic methods. Inspired by Noether's theorem.

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。

End-to-end small RNA-seq analysis from FASTQ to differential miRNA expression and target prediction. Use when analyzing miRNA, isomiR, tRF, or piRNA sequencing data through preprocessing, quantification, discovery, DE, and targets.

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。

Drug regulatory and approval research — FDA substance registry, ATC/EPC classification, EMA decisions, generic-drug status, FDA Orange Book exclusivity, NDA/BLA pathways. Use for jurisdiction-aware approval status (FDA vs EMA), generic vs brand availability, exclusivity expiry tracking, and regulatory pathway selection. Always specifies the market when reporting status.

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。

Automated LLM-driven hypothesis generation and testing on tabular datasets. Use when you want to systematically explore hypotheses about patterns in empirical data (e.g., deception detection, content analysis). Combines literature insights with data-driven hypothesis testing. For manual hypothesis formulation use hypothesis-generation; for creative ideation use scientific-brainstorming.

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。

Hybrid ML + physics binding affinity prediction. Empirical scoring, MM/GBSA rescoring, multi-method consensus, and batch virtual screening for protein-ligand complexes.

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Designs and analyzes stable-isotope-resolved metabolomics (SIRM / isotope tracing / fluxomics) experiments that measure metabolic ACTIVITY via 13C/15N/2H tracers, distinct from steady-state pool profiling. Covers tracer choice, isotopologue vs isotopomer, mass-isotopomer distributions (MID), fractional enrichment, the mandatory natural-abundance + tracer-purity correction (IsoCor, AccuCor), and the metabolic/isotopic steady-state vs non-stationary (INST-MFA) distinction. Use when feeding a labeled tracer and interpreting labeling patterns, correcting raw isotopologue intensities, computing or plotting an MID, or deciding tracing vs abundance profiling. For absolute pool concentration and MRM mechanics see metabolomics/targeted-analysis; for constraint-based genome-scale flux (FBA, not empirical tracing) see systems-biology/flux-balance-analysis; for feature detection see metabolomics/xcms-preprocessing; for pathway enrichment that ignores the pool-vs-flux caveat see metabolomics/pathway-mapping.

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。

Generates 3D conformer ensembles using RDKit ETKDGv3 with knowledge-enhanced distance geometry, MMFF94/UFF force-field optimization, CREST + GFN2-xTB semi-empirical refinement, and macrocycle-aware torsion preferences. Provides explicit decision rules for single vs ensemble conformer use, RMSD pruning, energy windows, conformer count, and force-field choice. Use when preparing 3D ligands for docking, generating descriptor input for 3D QSAR, or sampling macrocycle/peptide conformational ensembles.

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。