12,209 skills found · Page 334 of 407
aiworkskills / aws-wechat-article-main公众号运营｜微信公众号｜公众号一条龙｜公众号全流程｜自媒体运营｜wechat automation｜content pipeline｜AIGC workflow — 公众号一条龙运营总控入口，选题→写稿→审稿→排版→配图→发布串联 8 个子 skill，单条指令完成整篇图文从 0 到上架。面向公众号小编、自媒体、品牌内容。触发词分层：**一条龙流程**「一条龙」「完整流程」「从头做」「从 0 到发布」；**新做新发**「帮我写篇公众号文章」「做一篇公众号文章」「我想发一篇」「帮我发一篇」「再来一篇」；**选题起点**「今天写什么好」「有什么好写的」「找个话题」「爆款选题」「热点选题」「起个爆款…
aiworkskills / aws-wechat-article-assets公众号素材｜业务资料库｜预设包｜.aws 预设包｜主题包｜品牌包｜aiworkskills.cn — 用户业务资料库与预设包管理：业务资料按产品名组织在 `.aws-article/products/{产品名}/`（介绍 .md 直挂产品根 + 配图归 `images/` 子目录含同名说明 .md），AI 与用户对话产出业务介绍内容时引导用户保存；图片入库走 `product_image_ingest.py --product <产品名> --stem <中文名>`。导入 .aws ZIP 预设包（本地文件或 `https://aiworkskills.cn/**/*.aws` URL）合并主…
aiworkskills / aws-wechat-article-publish公众号发布｜公众号草稿箱｜公众号群发｜图文推送｜微信 API｜wechat automation｜WeChat API automation｜auto publish｜scheduled publish — 公众号 API 发布工具，图文入草稿箱或直接群发，支持封面素材上传、发布前检查与 draft/published 模式切换。面向公众号运营、自动化内容团队、开发者。触发词：「发布」「提交」「群发」「推送」「发出去」「上传到公众号」「发到公众号」「可以发了吗」「发布前检查」。需要多环节串联（写+审+排+配图+发）请走 aws-wechat-article-main。
aiworkskills / aws-wechat-article-topics公众号选题｜爆款标题｜热点追踪｜系列策划 — 公众号 AI 选题与标题生成，覆盖热点调研、选题策划、起标题、写摘要、系列排期。面向自媒体编辑、内容运营。触发词（**单独触发仅限对已有标题/摘要的修改**）：「改标题」「换个标题」「重起标题」「优化标题」「标题再想想」「换个标题试试」「改摘要」「重写摘要」「优化摘要」「摘要再优化下」。新做选题、起新标题、策划系列/内容日历、追热点都请走 aws-wechat-article-main；需要多环节串联（写+审+排+配图+发）也走 main。
aiworkskills / aws-wechat-sticker公众号贴图｜九宫格｜多图推送｜图片消息｜表情包 — 贴图与多图推送：从创意构思、规划图序、AI 生图到整组图审核，产出一组风格统一的图片 + 每张配文。发布走常规图文链路（拼成图文后 formatting + publish），微信原生「图片消息」需在公众号后台手动发。面向公众号运营、自媒体、IP 账号。触发词：「贴图」「多图推送」「发组图」「图片消息」「九宫格」「做一组图」「图片帖子」「发几张图」「不写正文发图」「只发图不写字」。是文章内配图/封面请走 aws-wechat-article-images；需要多环节串联（写+审+排+配图+发）请走 aws-wechat-article-mai…
firecrawl / firecrawl-monitorAlert by webhook/email on web changes — use for "monitor/watch/track/alert me when": recurring checks on known URLs (prefer over repeated one-off scrapes) or web-wide watches for new results (queries + goal).
firecrawl / firecrawl-agentAutonomously navigate websites and extract structured data across pages
firecrawl / firecrawl-interactDrive a live browser on a scraped page: click, fill forms, log in, paginate, infinite-scroll
firecrawl / firecrawl-alexandriaFind a direct path to structured data through ready-made workflows, data APIs, and indexes. Follow the search skill to discover and inspect tools, then the scrape skill to execute them.
firecrawl / firecrawl-developer-indexSearch an index of public repositories, GitHub issues, merged pull requests, repository READMEs, and curated documentation sites
firecrawl / firecrawl-research-indexFind the papers that answer a research query in Firecrawl's research paper index — a corpus of paper abstracts whose largest share is biomedical and life-science literature (PubMed, bioRxiv, medRxiv), alongside arXiv preprints in CS, physics, and math — using semantic search, semantic and structural…
7onez / cti-expertCTI Expert — Cyber Threat Intelligence & OSINT analysis skill for Claude Code / Codex. 120+ commands, 57 techniques, 79 typed MCP tools, deterministic case pipeline + ICD-203 reports. No API keys required for core.
nWave-ai / nw-at-completeness-checkCanonical AT completeness gate — research-anchored 7-category taxonomy (C1-C7) + 15-item mechanical checklist. Paradigm-neutral. Drives acceptance-designer reviewer verdict deterministically.
nWave-ai / nw-bdd-requirementsBDD requirements discovery methodology - Example Mapping, Three Amigos, conversational patterns, Given-When-Then translation, and collaborative specification
nWave-ai / nw-rigorSelects a quality-vs-token-consumption profile (lean, standard, thorough, exhaustive, custom, inherit) and persists it globally (~/.nwave/global-config.json) or per-project (.nwave/des-config.json)
nWave-ai / nw-tdd-methodologyDeep knowledge for Outside-In TDD - double-loop architecture, ATDD integration, port-to-port testing, walking skeletons, and test doubles policy
nWave-ai / nw-tdd-review-enforcementTest design mandate enforcement, test budget validation, TDD phase validation (3-phase canon per ADR-025), and external validity checks for the software crafter reviewer
nWave-ai / nw-test-design-mandatesDesign mandates for acceptance tests - hexagonal boundary, business language abstraction, user journey completeness, pure function extraction, 3 Pillars (domain language / chained narrative / production composition), and the layered ATD discipline (Universe-bound assertion, layer-dependent PBT mode,…
nWave-ai / nw-test-optimizationMethodology for minimizing test count while maximizing behavioral coverage - behavior definition, anti-pattern catalog, consolidation patterns, stopping criterion, coverage-preserving validation
nWave-ai / nw-bdd-methodologyBDD patterns for acceptance test design - Given-When-Then structure, scenario writing rules, pytest-bdd implementation, anti-patterns, and living documentation
nWave-ai / nw-cicd-and-deploymentCI/CD pipeline design methodology, deployment strategies, GitHub Actions patterns, and branch/release strategies. Load when designing pipelines or deployment workflows.
nWave-ai / nw-command-design-patternsBest practices for command definition files - size targets, declarative template, anti-patterns, and canonical examples based on research evidence
nWave-ai / nw-ddd-event-modelingEvent Modeling facilitation technique — brainstorm events, identify commands and views, define aggregate boundaries, write Given-When-Then specifications
nWave-ai / nw-divergeGenerates 3-5 divergent design directions through JTBD analysis, competitive research, structured brainstorming, and taste evaluation before convergence
nWave-ai / nw-executeUse when a DELIVER roadmap already exists and you need to dispatch exactly one identified step through its TDD cycle. Use nw-roadmap to create the plan, nw-deliver for the whole wave, and nw-continue to resume at the next inferred step.
nWave-ai / nw-finalizeArchives a completed feature to docs/evolution/, migrates lasting artifacts to permanent directories, and cleans up the temporary workspace. Use after all implementation steps pass and mutation testing completes.
nWave-ai / nw-jtbd-bdd-integrationTranslating JTBD analysis to BDD scenarios - job story to Given-When-Then patterns, forces-based test discovery, job-map-based test discovery, and property-shaped criteria
nWave-ai / nw-jtbd-coreCore JTBD theory and job story format - job dimensions, job story template, job stories vs user stories, 8-step universal job map, outcome statements, and forces of progress
nWave-ai / nw-jtbd-workflow-selectionJTBD workflow classification and routing - ODI two-phase framework, five job types with workflow sequences, baseline type selection, workflow anti-patterns, and common recipes
nWave-ai / nw-roadmap-designRoadmap concision rules, step decomposition efficiency, AC abstraction guidelines, and step-to-scenario mapping. Load when creating implementation roadmaps.
