「ema」の検索結果

Design a color palette with semantic tokens for a brand or product. Use when asked to "design a color palette", "what colors should we use", or "define semantic color tokens".

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。

Data engineer — databases, migrations, pipelines, schema design, and query optimization. Use when asked to "design a schema", "write a migration", "build a data pipeline", or "optimize this query".

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。

Data quality and pipeline health check — freshness, schema drift, null rates, orphaned records, pipeline status. Use when asked about "data quality check", "pipeline health", "is our data fresh", or "schema drift".

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。

Database reconnaissance — full inventory of schema, migrations, data volume, backups, connection pooling, and query patterns. Use when asked to "assess this database", "understand the schema", or "database health check".

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。

Information architecture — design navigation structure, content hierarchy, sitemap, and taxonomy for a product or feature set. Use when asked to "organize the navigation", "information architecture", "how should content be structured", "sitemap", "nav redesign", "where should X live", or "content hierarchy".

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 a data validation pipeline — schema checks, range validation, and quality metrics. Use when asked to "validate incoming data", "add schema checks", or "define data quality metrics".

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 forecasting model for a time series — demand, revenue, or usage prediction. Use when asked to "forecast demand", "predict next quarter revenue", or "build a time series model".

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 guide for mathematical formal verification, SMT solver constraints (Z3, Dafny, TLA+), invariant theorem proving for FinTech billing state machines, RBAC/ABAC authorization, and zero-violation architecture / Panduan ahli verifikasi formal matematis, SMT solver (Z3, Dafny, TLA+), pembuktian invarian state machine billing FinTech, otorisasi RBAC/ABAC, dan arsitektur zero-violation.

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 guide for AI FinOps, dynamic model routing (LiteLLM, Portkey, RouteLLM), cost optimization, budget enforcement, semantic caching, and latency-based fallback architectures / Panduan ahli untuk AI FinOps, routing model dinamis, optimasi biaya, penegakan anggaran, semantic caching, dan arsitektur fallback berbasis latensi.

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。

Define semantic type detectors in detectors.js for auto-detecting column data meaning

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。

Semantic HTML5, SEO basics, alt text, progressive enhancement and SPA concerns. Use when building web UI, reviewing markup or optimising for search.

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。

モデル駆動型アプリを Dataverse Web API（appmodules / sitemaps テーブル）で作成・構成・公開する。

Calculus, series, numerical methods, and optimization for computational mathematics. Covers limits (epsilon-delta, L'Hopital, squeeze theorem), derivatives (rules, optimization, related rates), integrals (Riemann sums, Fundamental Theorem of Calculus, integration techniques), series (convergence tests, Taylor and Maclaurin expansions), differential equations (separable, linear, exact), numerical methods (Newton-Raphson, Euler method, Simpson's rule), and computational pitfalls (floating-point arithmetic, catastrophic cancellation, numerical stability). Use when computing derivatives, integrals, limits, series, solving differential equations, or analyzing numerical accuracy.

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。

Proof writing and verification techniques for mathematical reasoning. Covers 13 proof strategies with canonical worked examples — direct, contrapositive, contradiction, cases, WLOG, vacuous/trivial, biconditional, counterexample, existence (constructive and non-constructive), uniqueness, induction (weak, strong, structural), pigeonhole/double-counting, and diagonal argument/invariants. Use when writing, verifying, or selecting proof strategies for any mathematical claim.

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。

Conjecture generation, sequence analysis, and experimental mathematics for mathematical discovery. Covers sequence analysis (OEIS lookups, recurrence relations, generating functions), pattern detection methods (finite differences, ratio analysis, modular patterns), conjecture generation workflow, classical integer sequences (Fibonacci, Catalan, partition numbers, Bernoulli numbers), combinatorial identities, the probabilistic method (Erdos, expected value arguments, Lovasz Local Lemma), AI-assisted discovery (FunSearch, Ramanujan Machine), and confidence calibration with cautionary tales (Mertens conjecture, Polya conjecture). Use when discovering patterns, analyzing sequences, generating conjectures, or working with combinatorial identities.

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。

Recognition and mitigation of systematic reasoning errors documented in the heuristics and biases tradition. Covers confirmation bias, availability, anchoring, representativeness, framing effects, hindsight bias, overconfidence, and motivated reasoning. Each bias is presented with its mechanism, diagnostic signal, and structured mitigation. Use when you suspect your own or another reasoner's conclusions may be shaped by systematic cognitive distortion rather than evidence.

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 parallel agents in a convoy or across git worktrees hit a write conflict on shared state — a git tree, a config, or a shared document — and you must decide whether the conflict is semantically real. Classifies each conflicting hunk as independent (keep both), redundant (pick one), or a genuine clash (escalate), instead of blind locks, abort-and-retry, or escalate-everything. Sits ABOVE refinery-merge and NEVER blind auto-merges: it wraps an LLM judgment, defaults to escalate on any uncertainty, and unconditionally escalates any hunk touching .planning/, config, credentials, or safety-critical paths. Backed by CoAgent (arxiv 2606.15376v1). Triggers on write conflicts between parallel agents on shared repo state.

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。

Meta-mathematical connections, cross-domain synthesis, and the Complex Plane as a navigational tool. Classifies problems by quadrant (Abstract/Embodied x Logic/Creativity), routes them to relevant domains, and traces dependency chains. Use when classifying mathematical problems across domains, navigating the Complex Plane of Experience, finding cross-domain connections, or building multi-domain solution strategies.

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。

Apply PostgreSQL schema, migration, and query patterns with idempotent SQL. Use when writing database schemas or migrations.

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 MaaFramework Pipeline nodes and recognition snippets from screenshots or observed UI state. Use for OCR node generation, ROI sweep, choosing TemplateMatch/OCR/ColorMatch/CustomRecognition, preserving target-file schema style, and designing `next`/`[JumpBack]` links before merging generated nodes into pipeline JSON.

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 wants to write, rewrite, or improve marketing copy for any page — including homepage, landing pages, pricing pages, feature pages, about pages, or product pages. Also use when the user says "write copy for," "improve this copy," "rewrite this page," "marketing copy," "headline help," or "CTA copy." For email copy, see email-sequence. For popup copy, see popup-cro.

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。

Claude Code runs an Emacs daemon, starts a CRDT server, shares buffers.

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。

Tour of Alice's heavily-customized terminal Emacs — Causal transients, Worlding org, proof tooling, MLX chat, voice, and clipboard.

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 semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.

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。