Prompt-driven capabilities that teach an agent new workflows. Every skill here is evaluated before it is listed.
Ranked by GitHub stars. Search to find fast, or page through the full list.
Analyze Claude Code sessions to learn what went right/wrong and suggest high-confidence improvements to skills. Use when asked to analyze a session, learn from a session, or review workflow effectiveness.
Harden a manifest-dev task guidance file for one-shot quality — either /define's quality-gate/Default set or figure-out's probe set. Iterates: orthogonality gap analysis, user-approved additions, prompt review, fix, converge. Use when a task file needs comprehensive coverage or "harden task file".
Use when the user wants to turn a static scene, character images, aerial map, drawn path, or route-control image into an immersive first-person FPV AI video prompt, especially Seedance/Kling/Runway/Veo style one-shot videos with numbered stop markers, red-line path control, world-map flythroughs, camera route planning, variable character counts, non-human POVs such as drones, pets, robot vacuums, character references, timed interactions, dialogue, spatial audio, and negative constraints.
Iteratively optimizes prompts for token efficiency by maximizing information density - reduces verbosity, removes redundancy, tightens phrasing while preserving semantic content. Use when asked to compress, shorten, reduce tokens, tighten, maximize density, increase information density, or make a prompt more concise.
Sync the prompt-engineering plugin from a local clone of claude-code-plugins into .claude/ so the repo is self-contained for isolated/web environments. Copies agents/skills, removes only previously-synced items that disappeared upstream. Other content in .claude/ is left alone. Use when asked to sync claude-code-plugins, pull prompt-engineering, refresh prompt-engineering plugin.
VMware vCenter/ESXi AI-powered monitoring and operations.
Generate multi-CLI distribution packages from the Claude Code plugin. Converts shared skills and package assets for OpenCode, Codex CLI, and Pi under dist/. Run after changing plugin components to keep distributions in sync.
한국 스타트업·1인 법인 대표·프리랜서·개인사업자를 위한 장부 자동 생성 진입점 스킬. 호출 시 5개 하위 스킬(jangbu-import·jangbu-tag·jangbu-tax·jangbu-dash·jangbu-jongso)을 번호·문자 메뉴로 제시하고, 입력 즉시 해당 스킬 인터뷰로 직행한다. 엑셀·5대 은행 CSV·7대 카드사 명세서 PDF·영수증·세금계산서 지원, macOS Vision/PaddleOCR 로컬 처리, Level 2 민감정보 마스킹.
Convert a codebase into a self-contained HTML portal app for ingestion into AI application systems. Produces a single deployable HTML file with embedded CSS, JS, and data.
Design RESTful APIs with best practices for consistency and usability
Build in verifiable increments. Never implement more than can be tested right now. Ship partial working systems over complete broken ones.
Provides coding assistance with best practices and code review
Systematic debugging approach for identifying and fixing issues
Graceful degradation and meaningful error messages. Errors are first-class citizens, not afterthoughts. Every error path is designed, not discovered.
Write thorough tests following TDD and BDD principles
Safe, behavior-preserving code transformation backed by tests. Refactor with evidence, not instinct.
Transforms imperative instructions into declarative goals with verifiable success criteria. Enables autonomous looping until verified completion.
Ghost personas review your code before it ships.
Accessible, performant, responsive UI patterns. Component design, state management discipline, and Core Web Vitals compliance.
Patterns for Retrieval-Augmented Generation (RAG) and agent memory systems. Retrieves only relevant context, prevents context bloat, and maintains coherent state across sessions.
精细化 AI 短剧 IP 创作技能（v0.6.0）。三阶段架构：Phase 1 创作（剧本+ref图，反复迭代）→ Phase 1.5 分镜图（每 grid 1-4 张候选静态图 = 视频首帧，工业级核心层）→ Phase 2 出片（按集解锁，4 模自动选）。v0.6.0 关键升级：① ref 库工艺偏置铁律（现代摩天楼易拟物，古建筑必出 chibi 人体，前期 IP 设计阶段就要避坑）② 即梦 5.0 失败模式 + 敏感词清单（3 类 fail 区分 / prompt 1500 字硬上限 / 反派词替换表 / 暧昧词清单）③ 分镜图 8 段 prompt 模板（CHARACTER/BACKGROUND/ACTION/SCENE/CAMERA/LIGHT/TEXT/STYLE）+ NOT humans 子句必加。沿用 v0.3.0 升级：Phase 1.5 分镜图层、4 模视频、ref 5-8 最优。v0.2.0：bash → Python subprocess、36 grid × 4-10s 变奏、红果必爆 7 招、工业级 ref 库 80-150 张、单 prompt 300-500 字。务必触发：用户提到短剧、微短剧、竖屏剧、AI 短剧、AI 漫剧、剧本创作、分镜、即梦/Seedance 出片、红果/番茄/抖音 IP 改编、爽剧、重生、穿越、赘婿、追妻、神医相师、AI 漫剧奇观、或"帮我做一部短剧"类请求。
Distill complex topics into layered, actionable summaries. Start with the key insight, layer in detail, end with recommended next action.
Load minimum necessary context into agent context windows. Prevents token bloat, reduces cost, and improves focus. Only load what the current task needs.
Create dark-themed, animated technical diagrams as self-contained HTML+SVG files — flowcharts whose connectors visibly flow, and architecture diagrams where requests travel as light dots through the system (Diagrid/Temporal landing-page style). Use this skill whenever the user asks for a flowchart, workflow, pipeline, process diagram, state machine, system architecture, infrastructure, cloud, microservices, or network topology diagram — and especially when they mention "animated", "flowing", "dynamic", "alive", "GIF-like", or want a diagram for a landing page, README, docs, or product demo. Also use it to convert Mermaid source (a mermaid code block or .mmd file) into an animated diagram — "animate this mermaid", "make this flowchart move". Prefer this over static diagram output whenever the diagram represents anything that moves: requests, events, data, jobs, messages, or control flow.
Structured logging, distributed tracing, and alerting for AI systems and traditional services. You can't fix what you can't see.
Document decisions, not just implementations. ADRs for architectural choices, inline docs for non-obvious code, and runbooks for operational knowledge.
APIClaw Skills - AI Agent capabilities for Amazon Product Research
Converts vague ideas into concrete, testable specifications with acceptance criteria. No implementation begins without a spec.
Measure first, optimize second. Data-driven performance improvements with before/after benchmarks and production validation.
Download YouTube video transcripts with automatic frame extraction for visual references. Use when analyzing YouTube videos, tutorials, or conference talks.
Get layered, context-aware explanations of unfamiliar code. Understand what it does, why it was written that way, and how to work with it safely.
Guards AI agents and LLM-powered applications against prompt injection attacks — both direct and indirect. Validates AI inputs and outputs at every trust boundary.
APIClaw Skills - AI Agent capabilities for Amazon Product Research
Designs and coordinates multi-agent pipelines where specialized agents collaborate to complete complex tasks. Includes communication protocols, failure handling, and state management.
Validates, parses, and sanitizes AI-generated outputs before they reach end users or downstream systems. Structured output enforcement, schema validation, and fallback handling.
This skill provides JavaScript coding standards and is automatically loaded for JavaScript projects. It includes modern ES2025 patterns, async handling, and recommended tooling.
Automated quality gates from commit to production. Every merge to main is potentially shippable. No manual steps in the deployment path.
Detects and mitigates LLM hallucinations in production pipelines. Validates AI-generated facts, code, and decisions before they reach end users or downstream systems.
Graph-based long-term memory skill for AI (LLM) coding agents — faster context, fewer tokens, safer refactors
Test real system boundaries, not mocks of mocks. Integration tests verify that components work together, not that they work in isolation.
Zero-downtime deployments with pre-flight checks, staged rollouts, and rollback plans. Never ship to production without a verified rollback strategy.
Gradle build tool standards focusing on Kotlin DSL. Covers project configuration, dependency management, and custom plugin/task development with Gradle 9 LTS.
Converts unstructured meeting notes into structured, assigned, time-bounded action items. Never leave a meeting without knowing who does what by when.
Systematic root cause analysis for production and development bugs. Hypothesis-driven debugging — never guess-and-check.
APIClaw Skills - AI Agent capabilities for Amazon Product Research
APIClaw Skills - AI Agent capabilities for Amazon Product Research
AI agent skills for drafting and scheduling social media posts via Typefully
APIClaw Skills - AI Agent capabilities for Amazon Product Research