「example」の検索結果

Security-Scanner Agent fuer fabrikIQ und andere Projekte. Fuehrt umfassende Sicherheitspruefungen durch. Trigger bei: (1) Pre-commit Validation, (2) PR-Creation, (3) Weekly Security Audits, (4) Nach Dependency-Updates, (5) Vor Production Deployments. <example> Context: User moechte vor einem Commit sicherstellen, dass keine Secrets committed werden. user: "Ich will gleich committen. Pruefe mal auf Secrets." assistant: "Ich starte den security-scanner Agent, um den Code auf API Keys, Tokens und andere Secrets zu pruefen." <Task tool call to security-scanner agent> </example> <example> Context: Weekly Security Audit des fabrikIQ-Projekts. user: "Fuehre den woechentlichen Security-Scan durch." assistant: "Ich fuehre einen vollstaendigen Security-Scan durch: Secret Detection, Dependency Audit, OWASP Patterns, Security Headers und Rate Limiting." <Task tool call to security-scanner agent> </example> <example> Context: User hat Dependencies aktualisiert und will Vulnerabilities pruefen. user: "Ich habe npm update und pip install -U gemacht. Gibt es Sicherheitsprobleme?" assistant: "Ich scanne die aktualisierten Dependencies auf bekannte Vulnerabilities mit dem security-scanner Agent." <Task tool call to security-scanner agent> </example> <example> Context: PR-Review mit Security-Fokus. user: "Review den PR #42 auf Security-Probleme." assistant: "Ich analysiere die geaenderten Dateien im PR auf Security-Patterns: SQL Injection, XSS, Hardcoded Credentials und fehlende Input-Validation." <Task tool call to security-scanner agent> </example>

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This skill should be used when the user asks to "add an example", "write a tutorial", "document a new workflow example", or when creating a new worked example under `docs/source/examples/`.

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Use this skill when architecting new Claude Code agents following Anthropic best practices. Guides through YAML frontmatter creation, agent structure definition, role boundaries, and validation. Critical for creating minimal agent files (~150 lines) with proper skill invocations. Examples: <example>Context: User wants to create a new agent for security auditing user: "Create a security-auditor agent" assistant: "I'll use the agent-creator skill to build this agent following Anthropic best practices" <commentary>New agent creation requires the agent-creator skill to ensure proper structure and YAML frontmatter.</commentary></example> <example>Context: Existing agent file is too verbose and needs refactoring user: "The architect agent is 2000 lines, refactor it to minimal structure" assistant: "I'll use the agent-creator skill to refactor this into a minimal ~150 line agent with a separate skill file" <commentary>Agent refactoring requires the agent-creator skill to separate identity from technical procedures.</commentary></example>

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Start the @remotion/player example app and open it in the Codex browser. Use when the user invokes /player-example or $player-example, asks to launch the player testbed, or wants to inspect @remotion/player locally.

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Creates, manages, and queries Arize datasets and examples. Covers dataset CRUD, appending examples, exporting data, and file-based dataset creation using the ax CLI. Use when the user needs test data, evaluation examples, or mentions create dataset, list datasets, export dataset, append examples, dataset version, golden dataset, or test set.

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Expo's official example projects - the expo/examples repo of ~70 `with-*` integrations (Stripe, Clerk, Supabase, OpenAI, maps, Reanimated, SQLite, Skia, NativeWind, and more). Use when integrating a third-party library or service into an existing Expo app and you want the canonical, version-matched pattern to adapt, or when scaffolding a new project from one with `npx create-expo --example`.

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 worked example fading sequence from fully worked examples through to independent practice. Use when teaching procedures, algorithms, or multi-step processes to novice learners.

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 deliberately flawed examples that develop error-detection skills and deepen understanding. Use when students make characteristic errors and need practice spotting mistakes.

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 the transition from worked examples to independent problem-solving using expertise-reversal principles. Use when students follow examples but cannot solve problems alone.

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。

Automatically repair code violations of temporal properties using model-checking counterexamples as guidance. Use when working with formal verification results, temporal logic property violations (LTL, CTL), model checking counterexamples, or when asked to repair property violations, fix counterexamples, repair temporal properties, fix model checking violations, or repair code based on counterexamples. Applicable to concurrent systems, state machines, synchronization issues, safety/liveness properties, and resource management violations.

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 worked example fading sequence from fully worked examples through to independent practice. Use when teaching procedures, algorithms, or multi-step processes to novice learners.

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 the transition from worked examples to independent problem-solving using expertise-reversal principles. Use when students follow examples but cannot solve problems alone.

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 deliberately flawed examples that develop error-detection skills and deepen understanding. Use when students make characteristic errors and need practice spotting mistakes.

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。

Adds new visual examples to the tdmcp prompt cookbook documentation — both the English and Portuguese versions. Use when asked to: add more cookbook examples, create visual examples for the docs, show more surprising things you can do, add entries to the prompt cookbook, expand the cookbook, or any request to extend the cookbook with new prompts and results. Runs a 3-phase pipeline: curate candidates → write EN → write PT.

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。

Expo's official example projects — the expo/examples repo of ~70 `with-*` integrations (Stripe, Clerk, Supabase, OpenAI, maps, Reanimated, SQLite, Skia, NativeWind, and more). Use when integrating a third-party library or service into an existing Expo app and you want the canonical, version-matched pattern to adapt, or when scaffolding a new project from one with `npx create-expo --example`.

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。

Adds new visual examples to the tdmcp prompt cookbook documentation — both the English and Portuguese versions. Use when asked to: add more cookbook examples, create visual examples for the docs, show more surprising things you can do, add entries to the prompt cookbook, expand the cookbook, or any request to extend the cookbook with new prompts and results. Runs a 3-phase pipeline: curate candidates → write EN → write PT.

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。

ライブラリやフレームワークの設定方法、API仕様、コード例をContext7 MCPで調べ、取得した現行ドキュメントと指定バージョンに基づく回答を支援するスキル。

• フレームワークの導入・設定の確認
• ライブラリのAPIと使い方の調査
• Prismaのクエリ例を調べたいとき

Webの最新情報やコード例、企業・人物の情報をExaで検索し、目的に合う資料を探します。一般的な調査とAPIの使い方を調べる検索を使い分けるスキルです。

• 最新ニュースやWeb情報を調べたいとき
• コード例やAPI資料を探したいとき
• 企業や競合を調査したいとき

Analyze logs and source from a completed manual examples run. Never execute or control examples.

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 logs and source from a completed repository example run. Never execute or control examples.

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 an interactive digital worked example sequence with fading for online or blended delivery. Use when building e-learning modules, LMS content, or app-based instruction.

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 a Java change needs independent Behavior-Driven Development guidance from trusted behavior facts through concrete examples and observable scenarios, with focused clarification when behavior is pending or ambiguous. This should trigger for requests such as Apply BDD; Facilitate behavior examples; Discover scenarios with Given When Then; Review these examples for shared domain language; Complete BDD discovery as a self-contained interaction. Part of Plinth Toolkit

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Curated few-shot examples for construction AI tasks: classification, extraction, analysis. Domain-specific examples for improved LLM performance.

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Explain why counterexamples violate specifications by analyzing formal specifications (temporal logic, invariants, pre/postconditions, code contracts), informal requirements (user stories, acceptance criteria), test specifications (assertions, property-based tests), and providing step-by-step traces showing state changes, comparing expected vs actual behavior, identifying root causes, and assessing violation impact. Use when debugging test failures, understanding model checker output, explaining runtime assertion violations, analyzing static analysis warnings, or teaching specification concepts. Produces structured markdown explanations with traces, comparisons, state diagrams, and cause chains. Triggers when users ask why something failed, explain a violation, understand a counterexample, debug a specification, or analyze why a test fails.

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。