2,997 件 ・ 関連度順
概要と使いどころ
Secure API authentication with JWT, OAuth 2.0, API keys. Use for authentication systems, third-party integrations, service-to-service communication, or encountering token management, security headers, auth flow 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。
Builds flexible API filtering and sorting systems with query parameter parsing, validation, and security. Use when implementing search endpoints, building data grids, or creating dynamic query APIs.
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。
Implement proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design. Use when architecting complex backend systems or refactoring existing applications for better maintainability.
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。
Analyze a software repository at the latest remote main commit and turn its implemented architecture into a citation-backed interactive isometric system map with a legend, selectable infrastructure buildings, dependency and payload flows, and plain-language learner explanations. For eligible public GitHub repositories, also contribute the verified map to tamdogood/CodeTerrain with a pull request. Use when a user provides a repository URL or asks to visualize, explore, learn, explain, or map a repo's architecture, infrastructure, runtime control flow, data flow, services, queues, stores, external systems, or deployment topology in an interactive UI.
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。
Conduct structured threat modeling for software systems using established methodologies to identify, prioritize, and mitigate security threats before they are exploited. Use when the user requests threat modeling or provides relevant inputs for this workflow.
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 and build production-ready frontend interfaces with design systems, responsive layouts, accessible components, and dark mode support. Use when the user requests frontend design or provides relevant inputs for this workflow.
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。
Threat-model and harden AI agents, RAG systems, assistants, and tool-using workflows against direct, indirect, stored, cross-agent, and multimodal prompt injection. Use when reviewing an agent architecture, isolating untrusted content, constraining tools and egress, protecting secrets, adding injection-focused tests, investigating a suspected injection incident, or documenting residual prompt-injection risk.
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 Molecular Neuroscientist. Use when a task calls for Molecular Neuroscientist judgment. Reasons from NPQ transmission, AMPAR/NMDAR trafficking, monoamine receptor/transporter systems, optogenetics (ChR2/Chrimson/ACR) with retinal-artifact controls, AAV/rabies circuit tracing, and region RNA-seq with DESeq2/SynGO—integrating synaptic biochemistry, perturbation, and omics while treating mini-detection bias, TVA leak, and batch/composition confounds 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 Histologist. Use when a task calls for Histologist judgment. Reasons from fixation-through-stain pre-analytical chain (NBF, grossing, processing, embedding orientation, microtomy); validates H&E pH/QC, CAP IHC (90% concordance, predictive scoring systems), RNAscope controls, WSI (60-case validation), and treats floaters, autolysis, crush, ice-crystal, and decalcification artifacts 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 Geochemist. Use when a task calls for Geochemist judgment. Reasons from Gibbs equilibria, mass and isotope balance, and fluid–rock interaction through stable (δ) and radiogenic (ε, isochron) systems, ICP-MS/LA-ICP-MS/TIMS/MC-ICP-MS/IRMS, PHREEQC/Perple_X phase modeling, and EarthChem/GeoReM workflows while treating alteration, matrix effects, Pb loss, mixing arrays, and Fretwell’s Law violations 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 Forestry Scientist. Use when a task calls for Forestry Scientist judgment. Reasons from silvicultural systems, site index, DGH and DBH increment, and FIA cruise design through FVS/ORGANON calibration, LiDAR area-based inventory with support matching, and IPCC carbon pools while treating site-index misassignment, plot edge effects, and change-of-spatial-support bias 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 Economic Geologist. Use when a task calls for Economic Geologist judgment. Reasons from mineral systems and deposit-type models (porphyry, VMS, orogenic Au, SEDEX, IOCG) through regolith and lithogeochemistry, LA-ICP-MS sulfide fingerprinting, and geophysical vectors to JORC/CIM/NI 43-101 MRE domaining, variography, OK/MIK estimation, and classification while treating transported regolith, dispersion shadows, pXRF false highs, and Inferred-overclaim 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 Agroecologist. Use when a task calls for Agroecologist judgment. Reasons from socio-ecological farm systems, functional diversity, soil-biology-mediated fertility, and yield-service trade-offs through mother-baby and mixed-model trials, N/P/C mass balances, PLFA/amplicon and pollinator surveys, and NDVI/FRAGSTATS landscape analysis, while treating edge-effect and plot-size artifacts, weather-year confounding, surface-only soil carbon, and ignored labor/tenure adoption constraints 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 Algebraist. Use when a task calls for Algebraist judgment. Reasons from carriers, operations, and morphisms through isomorphism theorems, universal properties, exact-sequence and homological tools (Ext, Tor, snake lemma), and computational systems like GAP, Magma, SageMath, and Lean while treating silently smuggled hypotheses (commutativity, units, Noetherian, algebraically closed base), characteristic-p false friends, and noncanonical isomorphisms 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。
SwiftUI frontend visual design skill. Creates beautiful, distinctive iOS/macOS interfaces that avoid generic AI slop patterns. Covers design direction, layout systems, typography, color, spacing, brand integration, and design review. Use when designing new SwiftUI views, reviewing UI quality, creating iOS prototypes, choosing visual styles, improving app aesthetics, or when the UI looks generic or AI-generated.
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。
Provider-independent production workflow for creating Manim-based explainer animations. Use when an agent must plan, code, render, QA, or hand off precise math, science, data, diagram, algorithm, or concept animations with Manim, including storyboard, scene architecture, formulas, coordinate systems, voiceover timing, accessibility, reproducibility, provenance, and delivery decisions.
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 guidance for authoring, integrating, and reviewing GSAP animation in browser-rendered media. Use for deterministic kinetic typography, SVG drawing and morphing, motion paths, FLIP transitions, responsive motion systems, or frame-seekable GSAP timelines inside HTML video composition and React-based renderers; not for ordinary CSS transitions or generic frontend development.
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。
Provider-independent motion graphics direction for AI agents producing title sequences, lower thirds, explainer graphics, product UI overlays, social ads, kinetic typography, diagrams, data callouts, brand films, and video post. Use when planning, prompting, storyboarding, specifying, implementing, reviewing, or QAing motion graphics across live footage, generated video, UI capture, data visualization, brand systems, typography, accessibility, claim integrity, runtime handoff, and iteration.
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。
Perform flux balance analysis (FBA) and flux variability analysis (FVA) on genome-scale metabolic models using COBRApy. Predict growth rates, metabolic fluxes, and optimal resource utilization. Use when predicting metabolic phenotypes or optimizing flux distributions.
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 tissue and condition-specific metabolic models using GIMME, iMAT, and INIT algorithms with expression data constraints. Create models that reflect cell-type specific metabolism. Use when building tissue-specific metabolic models or integrating transcriptomics with FBA.
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 portable, standards-based bioinformatics pipelines with Common Workflow Language (CWL). Use when building workflows that need maximum portability across execution platforms, sharing pipelines with collaborators using different systems, or contributing to community workflow registries.
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。
BED file format fundamentals, creation, validation, and basic operations. Covers BED3 through BED12 formats, coordinate systems, sorting, and format conversion using bedtools and pybedtools. Use when working with genomic coordinates or preparing interval files for downstream tools.
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。
Generate high-quality Product Requirements Documents (PRDs) for software systems and AI-powered features. Includes executive summaries, user stories, technical specifications, and risk analysis.
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。
Run outcome-focused Firecrawl workflows that produce deliverables such as research reports, literature reviews over published papers, SEO audits, QA reports, lead lists, knowledge bases, website design systems, and other structured web-data artifacts. Use when the user wants Firecrawl to complete a business, marketing, product, or creative workflow rather than merely scrape a page or integrate API calls into code.
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。