1.8万 件 ・ 関連度順
概要と使いどころ
Expert-level genetics covering Mendelian inheritance, molecular genetics, mutations, linkage analysis, population genetics, epigenetics, and GWAS. Covers classical and modern approaches from Mendel to CRISPR.
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。
Expert-level immunology covering innate and adaptive immunity, antibody structure and function, T cell biology, immune evasion, vaccines, autoimmunity, and immunotherapy.
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。
Expert-level statistics knowledge. Use when working with probability distributions, hypothesis testing, regression, Bayesian statistics, statistical inference, experimental design, ANOVA, or statistical modeling. Also use when the user mentions 'p-value', 'confidence interval', 'hypothesis test', 'regression', 'ANOVA', 'chi-square', 't-test', 'Bayesian', 'maximum likelihood', 'statistical significance', 'correlation', 'normal distribution', or 'sampling distribution'.
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。
Expert-level complex analysis knowledge. Use when working with complex functions, holomorphic functions, Cauchy's theorem, contour integration, Laurent series, residues, conformal mappings, or analytic continuation. Also use when the user mentions 'holomorphic', 'analytic', 'Cauchy theorem', 'residue', 'contour integral', 'Laurent series', 'conformal map', 'Riemann mapping', 'Mobius transformation', 'harmonic function', 'entire function', or 'meromorphic'.
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。
Expert-level numerical methods knowledge. Use when working with root finding, numerical integration, numerical differentiation, interpolation, numerical linear algebra, ODEs, PDEs, or optimization algorithms. Also use when the user mentions 'Newton method', 'bisection', 'Runge-Kutta', 'finite difference', 'finite element', 'interpolation', 'numerical integration', 'quadrature', 'iterative solvers', 'condition number', 'round-off error', or 'truncation error'.
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。
Expert-level graph theory knowledge. Use when working with graph algorithms, network flows, matching, graph coloring, planar graphs, spectral graph theory, random graphs, or graph applications in computer science and networks. Also use when the user mentions 'shortest path', 'minimum spanning tree', 'network flow', 'bipartite matching', 'graph coloring', 'clique', 'independent set', 'vertex cover', 'planarity', 'graph isomorphism', 'adjacency matrix', or 'Laplacian'.
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。
Expert-level real analysis knowledge. Use when working with limits, continuity, differentiability, Riemann and Lebesgue integration, sequences and series of functions, metric spaces, measure theory, or functional analysis foundations. Also use when the user mentions 'epsilon-delta', 'uniform continuity', 'uniform convergence', 'Lebesgue integral', 'measure theory', 'sigma-algebra', 'Banach space', 'Hilbert space', 'completeness', 'compactness', 'Heine-Borel', or 'dominated convergence'.
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。
Use to run a depth-bounded self-correction loop (attempt → critic verdict → re-attempt) as a tunable test-time compute knob — a do-and-judge specialisation, default off, capability-gated.
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。
Use for multi-step / ambiguous / end-to-end work — refactor a whole module, drive a vague ticket to a verified result, plan+build+verify a migration; coordinates the reasoning chain across skills.
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 expanding a one-line idea into the 12-block Cinematic Scene Blueprint — optional dialogue + ambient. Triggers 'expand this scene', 'blueprint for X'. 11-block refine → video-director.
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。
Use when the user wants a security-maturity scorecard / posture assessment of a module — category ratings with evidence, not a vulnerability hunt. Also on 'wie sicher ist dieses Modul aufgestellt?'
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。
Security audit — vulnerability scan, pentest review, attack-surface sweep; explicit request only, not regular feature work. Pre-implementation threat pass → threat-modeling.
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。
Use when reviewing a README for accuracy, usability, and alignment with the actual repository. Detects invented content, broken setup steps, and structural issues.
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。
Use when decomposing a company objective into team OKRs, auditing a draft OKR tree, or stress-testing an existing one for measurability and laddering.
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。
Use when establishing what observability a project actually has — the four Golden Signals, required signal to detected implementation to evidence, and SLI/SLO provenance.
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。
Use when working with MCP (Model Context Protocol) servers — their tools, capabilities, and best practices for effective agent workflows.
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。
Paste a URL/snippet before you borrow it — detects its license, runs the derived compatibility policy, and drafts a provenance ledger entry — even before any code is written, not after
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 the offline (jscpd) and online (scanoss-py) similarity scanners on demand against a diff or path — the ONLY home of this repo's detection capability; no CI gate exists or ever ran it automatically
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。
Use when configuring Laravel Reverb — the first-party WebSocket server with Pusher protocol compatibility, horizontal scaling, and Pulse monitoring.
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 scoring a roadmap, PR review, ADR, or ticket for completeness — risk, tests, migration, maintainability. Dispatched by /refine-ticket, /adr-create, /review-changes; never auto-gates.
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。
Use when creating Laravel jobs, queued workflows, events, or listeners. Covers clear responsibilities, safe serialization, and retry/failure handling.
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。
Use when reading a contract for risk and constraint — clause shape, redline priority, what the contract actually binds. Triggers on 'review this contract', 'what does this MSA constrain'.
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。
Use when designing monitoring dashboards — visualization selection, layout principles, observability strategies (RED/USE/Golden Signals), and data storytelling.
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 running discovery interviews — question-bank build, bias audit, insight extraction. Triggers on 'audit my guide', 'extract insights from transcript', 'is my hypothesis falsifiable'.
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。