「eas」の検索結果

Improve unclear UX copy, error messages, microcopy, labels, and instructions to make interfaces easier to understand. Use when the user mentions confusing text, unclear labels, bad error messages, hard-to-follow instructions, or wanting better UX writing.

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。

Turn vague Acceptance Criteria into measurable checks and test assertions

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 explaining concepts at different expertise levels, moving between abstract principles and concrete implementation, identifying edge cases by testing ideas against scenarios, designing layered documentation, decomposing complex problems into actionable steps, or bridging strategy-execution gaps. Invoke when user mentions abstraction levels, making concepts concrete, or explaining at different depths.

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 requests information about academic benchmarks, datasets, or research papers, particularly in machine learning, deep learning, or logical reasoning domains. This skill enables systematic research of academic benchmarks by searching web sources, downloading and analyzing arXiv papers, extracting key metadata (number of tasks, training availability, difficulty levels), and compiling comparative summaries. It triggers on requests involving dataset comparisons, benchmark analysis, or academic paper research for table creation.

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 time-varying amplitudes. Use when user mentions ramp, time-varying, cyclic, pulse, or gradually increasing loads. Does NOT handle static constant loads.

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。

Error handling patterns and best practices for OneKey. Use when implementing try/catch blocks, handling async errors, showing error messages, or managing error states in UI. Triggers on error, try, catch, exception, throw, fail, failure, error handling, error boundary, useAsyncCall, toast, fallback, error 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。

[00] TnR ABSOLUTE RIGOR — Systemic Verification Doctrine. Forced cognitive exertion for high-stakes investigations. Mandates absolute deconstruction, mathematical proof chains, and ≥95% derived certainty. Zero-tolerance for heuristics or sentiment-based reasoning. Shortcuts are defined as intentional hallucinations.

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。

[23] UNDERSTAND. Consult external AI models when internal sources are exhausted. Build quality prompts using Prompt150 formula (Context + Query + Method + Style). Use when Loop150 exhausts internal sources, need real-world precedents, confidence <75%, or require reasoning from specialized AI models.

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 GitHub may have shipped a GraphQL schema update affecting timeline event unions (PullRequestTimelineItems / IssueTimelineItems), when the gh-timeline dispatcher fallback is hitting more than expected, before a gh-timeline release, or when the user requests phrases like "verify timeline coverage", "audit gh-timeline schema", "check for new timeline events", "GitHub schema changed". Walks through schema diff → patch → test update → live verification → optional fixture refresh, marking each spot where a human decision is required.

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。

Verification loop for Spring Boot projects: build, static analysis, tests with coverage, security scans, and diff review before release or PR.

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。

Codified expertise for demand forecasting, safety stock optimization, replenishment planning, and promotional lift estimation at multi-location retailers. Informed by demand planners with 15+ years experience managing hundreds of SKUs. Includes forecasting method selection, ABC/XYZ analysis, seasonal transition management, and vendor negotiation frameworks. Use when forecasting demand, setting safety stock, planning replenishment, managing promotions, or optimizing inventory 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。

Verification loop for Django projects: migrations, linting, tests with coverage, security scans, and deployment readiness checks before release or PR.

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。

X-ray any AI model's behavioral patterns — refusal boundaries, hallucination tendencies, reasoning style, formatting defaults. No API key needed.

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。

Amplify safe or boring designs to make them more visually interesting and stimulating. Increases impact while maintaining usability. Use when the user says the design looks bland, generic, too safe, lacks personality, or wants more visual impact and character.

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 user-facing App Store release notes from git history since the last tag.

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。

Track engagement metrics, measure campaign ROI, and analyze content performance across Instagram, Facebook, YouTube, and TikTok.

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。

Advogado especialista em todas as areas do Direito brasileiro: familia, criminal, trabalhista, tributario, consumidor, imobiliario, empresarial, civil e constitucional.

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 MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. The quality of an MCP server is measured by how well it enables LLMs to accomplish real-world tasks.

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。

Explains how OpenClaw, OpenShell, and NemoClaw form the ecosystem, NemoClaw's position in the stack, what NemoClaw adds beyond the community sandbox, and when to prefer NemoClaw versus integrating OpenShell and OpenClaw directly. Use when users ask about the relationship between OpenClaw, OpenShell, and NemoClaw, or when to use NemoClaw versus OpenShell. Trigger keywords - nemoclaw ecosystem, openclaw openshell, nemoclaw vs openshell, sandboxed openclaw, how nemoclaw works, nemoclaw sandbox lifecycle blueprint, nemoclaw overview, openclaw always-on assistants, nvidia openshell, nvidia nemotron, nemoclaw release notes, nemoclaw changelog.

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。

Scan recent git commits for changes that affect user-facing behavior, then draft or update the corresponding documentation pages. Use when docs have fallen behind code changes, after a batch of features lands, or when preparing a release. Trigger keywords - update docs, draft docs, docs from commits, sync docs, catch up docs, doc debt, docs behind, docs 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。

Runs the end-of-day maintainer handoff for NemoClaw. Checks version target progress, bumps stragglers to the next patch version, generates a QA handoff summary, and cuts the release tag. Use at the end of the workday. Trigger keywords - evening, end of day, EOD, wrap up, ship it, cut tag, handoff, done for the day.

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。

Enter explore mode - a thinking partner for exploring ideas, investigating problems, and clarifying requirements. Use when the user wants to think through something before or during a change.

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。

Add descriptions for new models from the HuggingFace router to chat-ui configuration. Use when new models are released on the router and need descriptions added to prod.yaml and dev.yaml. Triggers on requests like "add new model descriptions", "update models from router", "sync models", or when explicitly invoking /add-model-descriptions.

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 guidance for GRPO/RL fine-tuning with TRL for reasoning and task-specific model training

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。