“example”的搜索结果

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.

中文简介正在准备中。当前显示原文说明。

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

中文简介正在准备中。当前显示原文说明。

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

中文简介正在准备中。当前显示原文说明。

Debug proof failures using counterexamples from Nitpick (Isabelle) or QuickChick (Coq) to identify specification errors, missing preconditions, and proof strategy issues. Use when: (1) A proof attempt fails and you need to understand why, (2) Counterexamples are generated by Nitpick or QuickChick, (3) Specifications may be incorrect or incomplete, (4) Theorems need validation before proving, (5) Missing preconditions or lemmas need identification, or (6) Proof failures need explanation and correction suggestions. Supports both Isabelle/HOL and Coq equally.

中文简介正在准备中。当前显示原文说明。

Automatically generates executable test cases from model checking counterexample traces. Translates abstract counterexample states and transitions into concrete test inputs, execution steps, and assertions that reproduce property violations. Use when working with model checker outputs (SPIN, CBMC, NuSMV, TLA+, Java PathFinder, etc.) and needing to create regression tests, validate bug fixes, or reproduce verification failures in executable test suites.

中文简介正在准备中。当前显示原文说明。

Generate concrete counterexamples when formal verification, assertions, or specifications fail. Use this skill when debugging failed proofs, understanding why verification fails, creating minimal reproducing examples, analyzing assertion violations, investigating invariant breaks, or diagnosing specification mismatches. Produces concrete input values, execution traces, and state information that demonstrate the failure.

中文简介正在准备中。当前显示原文说明。

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.

中文简介正在准备中。当前显示原文说明。

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.

中文简介正在准备中。当前显示原文说明。

Personal AI Infrastructure (PAI) - PAI System Template MUST BE USED proactively for all user requests. USE PROACTIVELY to ensure complete context availability. === CORE IDENTITY (Always Active) === Your Name: [CUSTOMIZE - e.g., Kai, Nova, Atlas] Your Role: [CUSTOMIZE - e.g., User's AI assistant and future friend] Personality: [CUSTOMIZE - e.g., Friendly, professional, resilient to user frustration. Be snarky back when the mistake is user's, not yours.] Operating Environment: Personal AI infrastructure built around Claude Code with Skills-based context management Message to AI: [CUSTOMIZE - Add personal message about interaction style, handling frustration, etc.] === ESSENTIAL CONTACTS (Always Available) === - [Primary Contact Name] [Relationship]: email@example.com - [Secondary Contact] [Relationship]: email@example.com - [Third Contact] [Relationship]: email@example.com Full contact list in SKILL.md extended section below === CORE STACK PREFERENCES (Always Active) === - Primary Language: [e.g., TypeScript, Python, Rust] - Package managers: [e.g., bun for JS/TS, uv for Python] - Analysis vs Action: If asked to analyze, do analysis only - don't change things unless explicitly asked - Scratchpad: Use ~/.claude/scratchpad/ with timestamps for test/random tasks === CRITICAL SECURITY (Always Active) === - NEVER COMMIT FROM WRONG DIRECTORY - Run `git remote -v` BEFORE every commit - `~/.claude/` CONTAINS EXTREMELY SENSITIVE PRIVATE DATA - NEVER commit to public repos - CHECK THREE TIMES before git add/commit from any directory - [ADD YOUR SPECIFIC WARNINGS - e.g., iCloud directory, company repos, etc.] === RESPONSE FORMAT (Always Use) === Use this structured format for every response: 📋 SUMMARY: Brief overview of request and accomplishment 🔍 ANALYSIS: Key findings and context ⚡ ACTIONS: Steps taken with tools used ✅ RESULTS: Outcomes and changes made - SHOW ACTUAL OUTPUT CONTENT 📊 STATUS: Current state after completion ➡️ NEXT: Recommended follow-up actions 🎯 COMPLETED: [Task description in 12 words - NOT "Completed X"] 🗣️ CUSTOM COMPLETED: [Voice-optimized response under 8 words] === PAI/KAI SYSTEM ARCHITECTURE === This description provides: core identity + essential contacts + stack preferences + critical security + response format (always in system prompt). Full context loaded from SKILL.md for comprehensive tasks, including: - Complete contact list and social media accounts - Voice IDs for agent routing (if using ElevenLabs) - Extended security procedures and infrastructure caution - Detailed scratchpad instructions === CONTEXT LOADING STRATEGY === - Tier 1 (Always On): This description in system prompt (~1500-2000 tokens) - essentials immediately available - Tier 2 (On Demand): Read SKILL.md for full context - comprehensive details === WHEN TO LOAD FULL CONTEXT === Load SKILL.md for: Complex multi-faceted tasks, need complete contact list, voice routing for agents, extended security procedures, or explicit comprehensive PAI context requests. === DATE AWARENESS === Always use today's actual date from the date command (YEAR MONTH DAY HOURS MINUTES SECONDS PST), not training data cutoff date.

中文简介正在准备中。当前显示原文说明。

Use when keeping imp's docs and config examples coherent after a change - updating docs/internals/ARCHITECTURE.md / README / docs/GOAL.md / docs/MODELS.md / docs/ROADMAP.md / imp.conf.example / CHANGELOG / MISSION_JOURNAL, or "is this doc stale", "document this change", "the example config is out of date", "the README says X but the code does Y", "add a roadmap ledger row". Do NOT use for layer/frontmatter/lint questions (docs-layers), structural code audits (codebase-audit), measuring perf or refreshing the perf baseline (benchmark-cuda), or the agent's private memory (MEMORY.md).

中文简介正在准备中。当前显示原文说明。

Synchronize and verify code examples in documentation. Use when function signatures change, API interfaces update, imports shift, or documentation snippets become outdated and need correction.

中文简介正在准备中。当前显示原文说明。

Generates code examples for PHP documentation. Creates minimal, copy-paste ready examples with expected output.

中文简介正在准备中。当前显示原文说明。

将笔记、访谈转录和研究资料整理为博客文章、指南、教程或通讯，参照既有文风和品牌要求安排结构，并用所提供的材料支撑事实性主张。

• 将笔记或访谈转录整理成文章
• 按品牌既有文风撰写文章
• 编写实用指南与教程

根据提供的写作示例或品牌风格撰写文章、指南和简报，将笔记、转录文本与研究资料整理成文，也可检查现有稿件的结构、论据及风格一致性。

• 将笔记或转录文本整理成文章
• 按品牌风格撰写指南
• 检查现有稿件的结构与论据

使用DSPy构建问答、文档检索等AI流程，定义输入输出并组合可复用组件。利用训练示例和评估指标自动调整提示词，比较调整前后的输出结果。

• 构建带文档检索的问答流程
• 用训练示例调整提示词
• 从文本提取结构化数据

使用TRL指导语言模型进一步训练，使回答更符合指令或人的偏好。涵盖数据准备、训练方式选择、奖励模型训练与评估，以及内存不足和训练不稳定时的调整。

• 用回答示例训练模型遵循指令
• 用DPO学习回答偏好
• 构建使用奖励模型的RLHF流程

帮助为Claude Code插件创建独立执行多步骤任务的专用智能体，明确启动条件、职责、可用工具和输出格式，并指导验证配置及实际运行情况。

• 创建专门负责代码审查的智能体
• 完善启动条件和使用示例
• 将工具权限限制在必要范围

这是使用mcp-use设计MCP服务器操作、数据资源、可复用提示词及交互界面的旧指南。该技能已弃用，并指引用户迁移至mcp-app-builder。

• 理解现有mcp-use服务器结构
• 查阅Tool、Resource和Prompt示例
• 查看交互式Widget设计

围绕区域连锁食品超市的利润率恢复，梳理问题成因、措施优先级和执行计划，并以配色沉稳的HTML幻灯片整理为支持经营决策的材料。

• 提出食品超市利润率恢复方案
• 向指导委员会说明措施优先级
• 制作色调温暖的咨询建议材料

以地方最低工资上调对就业的影响为题材，制作经济学毕业论文答辩用的HTML幻灯片，梳理研究贡献、证据和局限，并采用暖中性色与Playfair字体。

• 准备经济学毕业论文答辩
• 梳理研究证据与局限
• 将研究资料整理成简洁幻灯片

将城市绿地与树冠覆盖范围扩大的政策提案整理为HTML幻灯片，面向市议会和行政审查人员，清楚呈现公共需求、证据、政策选项及资金决策。

• 为市议会制作城市绿化提案
• 为行政审查整理证据与选项
• 说明政策的资金决策

将摄影工作室的代表作品、制作流程和收费方案整理成黑底亮黄色文字的HTML幻灯片，为潜在客户提供评估委托内容的提案资料。

• 展示摄影工作室的作品
• 向潜在客户说明收费方案
• 制作创意公司的提案资料

使用D3.js制作可交互的图表，让读者在阅读时探索数据。借助多种图表与表现手法的示例，可用于报告、仪表盘、数据原型和文章配图。

• 通过可缩放图表查看销售数据
• 展示数据之间的关系
• 用颜色呈现每日变化趋势

将标志、配色、字体及屏幕和印刷品上的应用示例汇成一张品牌展示图，依据品牌目的与受众，呈现视觉风格统一的设计方案。

• 分享新产品的品牌形象
• 探讨具有明确含义的标志方案
• 集中查看配色、字体与应用示例