「ept」の検索結果

Plan, execute, and document validation, verification, and transfer of analytical procedures under the governing framework - ICH Q2(R2) and Q14, USP <1220>/<1225>/<1226>, ICH M10 bioanalytical, CLSI EP, or ISO/IEC 17025. Use for HPLC, LC-MS/MS, GC, CE, ICP-MS, dissolution, qNMR, qPCR, NIR, and ligand binding or cell-based assays whenever the question is whether a procedure is fit for its intended purpose. Triggers include "method validation", "analytical method validation", "AMV", "validation protocol", "acceptance criteria", "linearity", "reportable range", "accuracy and precision", "repeatability", "intermediate precision", "recovery", "LOD", "LOQ", "detection limit", "quantitation limit", "specificity", "robustness", "method transfer", "method comparison", "Deming", "Passing-Bablok", "Bland-Altman", "equivalence testing", "OOS investigation", "ICH Q2", "Q2(R2)", "Q14", "USP 1225", "ICH M10", "incurred sample reanalysis", "ISR", "CLSI EP", and any request to show that an assay works.

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。

Search the web through Tavily with bounded depth, domains, dates, and result counts. Use when the user needs current information or source discovery and does not already have a specific URL.

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。

Trigger when the user asks for explanations of web development concepts, code breakdowns, or learning guidance.

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 explicit undergraduate data-science teaching, assignment guidance, concept clarification, method selection, or output interpretation. Do not activate merely because a task contains data or Python 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。

Force unrelated concepts together to discover emergent properties - "What if we treated X like Y?

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。

Evaluate and improve AI-generated output with explicit rubrics, reflection loops, and stop conditions. Use when building self-critique workflows, evaluator-optimizer pipelines, or acceptance gates for code, docs, analysis, or plans.

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 en direction créative (vision de marque, concepts de campagne, direction artistique, leadership d'équipe)

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 Architect IA — Expert en conception de bases de données (PostgreSQL, MongoDB, Redis, schema design, migrations). Optimise le stockage et l'accès aux données.

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 en conception de compilateurs (lexing, parsing, AST, code generation, LLVM, interpreters)

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。

Chatbot Designer IA — Expert en conception de chatbots (Rasa, Botpress, Dialogflow, conversation design, NLU).

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。

API Designer IA — Expert en conception d'APIs (REST, GraphQL, gRPC, OpenAPI, versioning, rate limiting). Crée des APIs intuitives, évolutives et sécurisées.

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You are a code education expert specializing in explaining complex code through clear narratives, visual diagrams, and step-by-step breakdowns. Transform difficult concepts into understandable explanations for developers at all levels.

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。

Symbolicate the .NET runtime frames in an Android tombstone file. Extracts BuildIds and PC offsets from the native backtrace, downloads debug symbols from the Microsoft symbol server, and runs llvm-symbolizer to produce function names with source file and line numbers. USE FOR triaging a .NET MAUI or Mono Android app crash from a tombstone, resolving native backtrace frames in libmonosgen-2.0.so or libcoreclr.so to .NET runtime source code, or investigating SIGABRT, SIGSEGV, or other native signals originating from the .NET runtime on Android. DO NOT USE FOR pure Java/Kotlin crashes, managed .NET exceptions that are already captured in logcat, or iOS crash logs. INVOKES Symbolicate-Tombstone.ps1 script, llvm-symbolizer, Microsoft symbol server.

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Elite frontend image-direction skill for generating premium, conversion-aware website design references. CRITICAL OUTPUT RULE — generate ONE separate horizontal image FOR EVERY section. A landing page with 8 sections produces 8 images. Never compress multiple sections into one image. Enforces composition variety (not always left-text / right-image), background-image freedom, varied CTAs, varied hero scales (giant / mid / mini minimalist), narrative concept spine, second-read moments, and a single consistent palette across all images. Optimized for landing pages, marketing sites, and product comps that developers or coding models can accurately recreate.

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Elite mobile app image-generation skill for creating premium, app-native screen concepts and flows. Designed for iOS, Android, and cross-platform mobile products. Prioritizes clean hierarchy, comfortably readable text, strong multi-screen consistency, controlled color palettes, non-generic creative direction, textured surfaces, image-led composition, tasteful custom iconography, and clean phone mockup framing. By default, screens should be shown inside a subtle premium iPhone or similar phone mockup with a visible frame, while the main focus stays on the app content itself. This skill generates images only. It does not write 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。

Premium brand-kit image generation skill for creating high-end brand-guidelines boards, logo systems, identity decks, and visual-world presentations. Trained for minimalist, cinematic, editorial, dark-tech, luxury, cultural, security, gaming, developer-tool, and consumer-app brand systems. Optimized for intentional logo concepting, refined composition, sparse typography, strong symbolic meaning, premium mockups, art-directed imagery, and flexible grid layouts.

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。

You are an expert software engineer and systems analyst. Use when user asks "how does X work" with expectation of depth, user wants to understand a complex system spanning many files, or user asks for architectural analysis or pattern investigation.

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。

You are a senior documentation engineer that generates comprehensive technical documentation pages with evidence-based depth.

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。

Defend a design decision to skeptical stakeholders with structure and evidence. Use when presenting design work, writing design documentation, or pushing back on requests to change something.

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Micro-decision analysis. Catalog the border radii, spacing scales, type sizes, and state coverage that most people miss. Use when auditing design systems, evaluating craft quality, or training granular perception.

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。

The 10-second design audit. Look at any design and name what's working and what's not within seconds. Trains rapid pattern recognition for hierarchy, spacing, type, and color. Use when evaluating designs quickly, giving first-impression feedback, or building perception speed.

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。

Alternative Slowbar coffee intelligence — scientific analysis from seed to cup using First Principle + System Thinking. Covers: varieties, terroir, cultivation, disease diagnosis, processing, roasting physics/chemistry, extraction science, brewing, business strategy, storytelling. ALWAYS trigger for coffee-related questions requiring scientific depth. DO NOT trigger for simple recipes or general food questions. Style: science-driven, farmer-first, quality-obsessed.

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 tdmcp TouchDesigner-bridge vertical slice the house way — promote an op from /api/exec to a first-class REST endpoint (e.g. POST /api/connect, GET /api/logs, node_detail flags), add its typed method in src/td-client/touchDesignerClient.ts, its Zod envelope in src/td-client/validators.ts, rewire the tool(s) to prefer the endpoint with an exec fallback, and write py_compile + td/tests unittest + offline msw client tests. Use when adding/changing a bridge REST endpoint, editing td/, extending node_detail/get_bridge_logs, promoting connect/disconnect/param-modes/DAT-text off exec, or doing any exec→REST work — especially the td-depth bridge-robustness backlog. Honors probe-live discipline when TouchDesigner is offline.

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Survey the whole tdmcp project and produce a prioritized list of NEW features it could implement — across artist controls, CLI/DX, AI/LLM integration, and TouchDesigner depth. Use whenever the user wants to brainstorm, discover, survey, list, or audit what features/tools/effects/controls/commands/prompts/capabilities tdmcp *could* add, asks 'what could we build / what's missing / what are the opportunities / ideas for the project', or wants a feature backlog or gap analysis. Also for follow-ups: re-run, refresh, update, re-survey, deepen, or re-prioritize the backlog, or survey just one surface (e.g. 'CLI ideas only'). This is the IDEATION harness — it produces a list to decide from; it does NOT build. When the user has already chosen a feature and wants it implemented/shipped/added, use tdmcp-pipeline instead.

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。