- Nr.: 7.301
Repository: anthropics/knowledge-work-plugins
GitHub-Sterne: 35.244Aktualisiert: 13. März 2026
- Nr.: 7.302
Repository: breferrari/obsidian-mind
GitHub-Sterne: 5.515Aktualisiert: 19. Juli 2026
- Nr.: 7.303
Repository: davila7/claude-code-templates
GitHub-Sterne: 33.223Aktualisiert: 24. Okt. 2026
- Nr.: 7.304
Repository: davila7/claude-code-templates
GitHub-Sterne: 33.223Aktualisiert: 20. Dez. 2025
- Nr.: 7.305
article-fact-checker三层审查模型,逐段逐句验证文章真伪、证据链与逻辑结构。Use when the user asks to fact-check, verify, audit, or evaluate the credibility of an article, essay, report, opinion piece, social-media post, or any written claim — including checking logical consistency, evidence chains, source reliability, fabrication, non-quantifiable conclusions, and producing a scored report with original-text citations.Sprache des Skill-Inhalts: Chinesisch
Repository: digoal/blog
GitHub-Sterne: 8.603Aktualisiert: 3. Juli 2026
- Nr.: 7.306
Repository: DingTalk-Real-AI/dingtalk-openclaw-connector
GitHub-Sterne: 2.130Aktualisiert: 22. Apr. 2026
- Nr.: 7.307
Repository: Fission-AI/OpenSpec
GitHub-Sterne: 74.345Aktualisiert: 30. Okt. 2026
- Nr.: 7.308
Repository: hollandkevint/data-product-operator
GitHub-Sterne: 5Aktualisiert: 7. Apr. 2026
- Nr.: 7.309
Repository: LeoYeAI/openclaw-master-skills
GitHub-Sterne: 2.169Aktualisiert: 8. Juni 2026
- Nr.: 7.310
idapythonIDA Pro Python scripting for reverse engineering. Use when writing IDAPython scripts, analyzing binaries, working with IDA's API for disassembly, decompilation (Hex-Rays), type systems, cross-references, functions, segments, or any IDA database manipulation. Covers ida_* modules (50+), idautils iterators, and common patterns.Sprache des Skill-Inhalts: Englisch
Repository: mrexodia/ida-pro-mcp
GitHub-Sterne: 13.414Aktualisiert: 3. Jan. 2026
- Nr.: 7.311
Repository: netease-youdao/LobsterAI
GitHub-Sterne: 6.175Aktualisiert: 2. März 2026
- Nr.: 7.312
Repository: nexu-io/open-design
GitHub-Sterne: 106.688Aktualisiert: 14. Juli 2026
- Nr.: 7.313
Repository: nexu-io/open-design
GitHub-Sterne: 106.688Aktualisiert: 14. Juli 2026
- Nr.: 7.314
Repository: penghang1223/test-case-writer-plus
GitHub-Sterne: 3Aktualisiert: 18. Mai 2026
- Nr.: 7.315
Repository: career-ops-hq/career-ops
GitHub-Sterne: 81.282Aktualisiert: 1. Nov. 2026
- Nr.: 7.316
spaceos-terminalSpaceOS terminál kommunikációs skill. Használd amikor üzeneteket kell olvasni ("olvasd le az üzeneteidet", "olvasd el az inbox-odat", "van új feladatod?"), vagy amikor egy feladatot befejeztél és outbox üzenetet kell írni ("kész vagyok", "befejeztem", "írj DONE üzenetet"). A skill az összes SpaceOS terminálra vonatkozik — Kernel, Orchestrator, Infra, E2E, Portal, Joinery, Abstractions. Lefedi az inbox olvasás rituálját, a kötelező build+test gate-et, és a DONE/BLOCKED outbox sablonokat.Sprache des Skill-Inhalts: Ungarisch
Repository: Szantoi/spaceos-core
GitHub-Sterne: 0Aktualisiert: 11. Juli 2026
- Nr.: 7.317
Repository: TeamWiseFlow/xiaobei
GitHub-Sterne: 8.701Aktualisiert: 18. Okt. 2026
- Nr.: 7.318
Repository: affaan-m/ECC
GitHub-Sterne: 299.529Aktualisiert: 17. Mai 2026
- Nr.: 7.319
Repository: affaan-m/ECC
GitHub-Sterne: 299.529Aktualisiert: 17. Mai 2026
- Nr.: 7.320
Repository: affaan-m/ECC
GitHub-Sterne: 299.529Aktualisiert: 30. März 2026
- Nr.: 7.321
sddImplements the Spec-Driven Development lifecycle (Intent, Requirements, Design, Tasks, Build) for structured feature development. Use when the user wants to scaffold a new feature spec, generate EARS requirements, create a technical design, break work into tasks, or check spec status. Trigger on keywords: sdd, spec-driven, ears requirements, feature spec.Sprache des Skill-Inhalts: Englisch
Repository: brycewang-stanford/Auto-Empirical-Research-Skills
GitHub-Sterne: 4.955Aktualisiert: 3. Apr. 2026
- Nr.: 7.322
Repository: OpenMontageInc/OpenMontage
GitHub-Sterne: 78.816Aktualisiert: 29. März 2026
- Nr.: 7.323
Repository: kostja94/marketing-skills
GitHub-Sterne: 1.089Aktualisiert: 6. Nov. 2026
- Nr.: 7.324
Repository: anthropics/financial-services
GitHub-Sterne: 41.165Aktualisiert: 21. Mai 2026
- Nr.: 7.325
Repository: yipng05-max/-skills
GitHub-Sterne: 320Aktualisiert: 3. Apr. 2026
- Nr.: 7.326
Repository: affaan-m/ECC
GitHub-Sterne: 299.529Aktualisiert: 27. Sept. 2026
- Nr.: 7.327
Repository: borghei/Claude-Skills
GitHub-Sterne: 1.077Aktualisiert: 23. Okt. 2026
- Nr.: 7.328
web-search-scraper-api-skillThis skill helps users automatically extract complete Markdown content from any website via the BrowserAct Web Search Scraper API. The Agent should proactively apply this skill when users express needs like extract complete markdown from a specific website, scrape the content of an article link, get the text from a target url, convert a webpage to markdown format, fetch the main content of a blog post, extract data from a given web page, parse the html of a website into markdown, download the readable text from a news article, obtain the content of a tutorial page, extract all the markdown text from any http or https url, scrape documentation from a web link, or grab the text of a single webpage.Sprache des Skill-Inhalts: Englisch
Repository: browser-act/skills
GitHub-Sterne: 6.339Aktualisiert: 21. Apr. 2026
- Nr.: 7.329
Repository: BytePioneer-AI/openclaw-china
GitHub-Sterne: 3.948Aktualisiert: 17. März 2026
- Nr.: 7.330
Repository: chendongqi/OPB-Skills
GitHub-Sterne: 133Aktualisiert: 11. Feb. 2026
- Nr.: 7.331
humanizar-texto-esElimina patrones de escritura típicos de IA en textos en español de España para que suenen naturales y humanos. Aplica esta skill siempre que generes, edites o revises textos en español: artículos, guías, tutoriales, emails, copy comercial, publicaciones en redes sociales, documentación, informes o cualquier prosa. Actívala también cuando el usuario pida humanizar texto, eliminar tono robótico, mejorar la naturalidad de un texto, o cuando mencione que algo suena a IA, a ChatGPT o a texto generado automáticamente.Sprache des Skill-Inhalts: Spanisch
Repository: ComeOnOliver/skillshub
GitHub-Sterne: 58Aktualisiert: 23. März 2026
- Nr.: 7.332
Repository: davila7/claude-code-templates
GitHub-Sterne: 33.223Aktualisiert: 24. Okt. 2026
- Nr.: 7.333
Repository: davila7/claude-code-templates
GitHub-Sterne: 33.223Aktualisiert: 20. Dez. 2025
- Nr.: 7.334
Repository: deanpeters/Product-Manager-Skills
GitHub-Sterne: 7.932Aktualisiert: 10. Aug. 2026
- Nr.: 7.335
Repository: doccker/cc-use-exp
GitHub-Sterne: 1.061Aktualisiert: 30. Juni 2026
- Nr.: 7.336
Repository: ECNU-ICALK/AutoSkill
GitHub-Sterne: 610Aktualisiert: 16. März 2026
- Nr.: 7.337
Repository: github/awesome-copilot
GitHub-Sterne: 40.947Aktualisiert: 24. Feb. 2026
- Nr.: 7.338
Repository: hamzafarooq/claude-code-starter
GitHub-Sterne: 150Aktualisiert: 5. Juni 2026
- Nr.: 7.339
anti-ai-slop-writingProduces human-sounding text that avoids detectable AI writing patterns. Activates on any writing task — tweets, emails, articles, bios, captions, reports, copy, messages, LinkedIn posts, cover letters, README files, or any content where the output must not read as AI-generated. Enforces banned vocabulary, structural variety, punctuation discipline, accuracy rules, and voice calibration. Use when the user says "write," "draft," "rewrite," "make this sound human," "anti-slop," "not AI," or any variation of wanting authentic-sounding output.Sprache des Skill-Inhalts: Englisch
Repository: jalaalrd/anti-ai-slop-writing
GitHub-Sterne: 580Aktualisiert: 18. Apr. 2026
- Nr.: 7.340
Repository: kortix-ai/CompanyOS
GitHub-Sterne: 20.584Aktualisiert: 31. Juli 2026
- Nr.: 7.341
Repository: liangdabiao/liurun-bookwriter-skills
GitHub-Sterne: 285Aktualisiert: 11. Juli 2026
- Nr.: 7.342
Repository: manymore13/report-cli
GitHub-Sterne: 56Aktualisiert: 25. Mai 2026
- Nr.: 7.343
Repository: NanmiCoder/NewsCrawler
GitHub-Sterne: 636Aktualisiert: 8. Aug. 2026
- Nr.: 7.344
Repository: shadow1ng/fscan
GitHub-Sterne: 14.769Aktualisiert: 1. Okt. 2026
- Nr.: 7.345
Repository: vercel/next.js
GitHub-Sterne: 143.245Aktualisiert: 14. Mai 2026
- Nr.: 7.346
Repository: wonsukchoi/domain-experts
GitHub-Sterne: 24Aktualisiert: 15. Juli 2026
- Nr.: 7.347
Repository: wshobson/agents
GitHub-Sterne: 42.334Aktualisiert: 22. Mai 2026
- Nr.: 7.348
Repository: ChonSong/skill-retriever
GitHub-Sterne: 10Aktualisiert: 10. Juli 2026
- Nr.: 7.349
Repository: a5c-ai/babysitter
GitHub-Sterne: 1.891Aktualisiert: 1. Juni 2026
- Nr.: 7.350
Repository: affaan-m/ECC
GitHub-Sterne: 299.529Aktualisiert: 22. März 2026
- Nr.: 7.351
Repository: affaan-m/ECC
GitHub-Sterne: 299.529Aktualisiert: 11. Mai 2026
- Nr.: 7.352
Repository: affaan-m/ECC
GitHub-Sterne: 299.529Aktualisiert: 12. Aug. 2026
- Nr.: 7.353
Repository: alchaincyf/huashu-md-html
GitHub-Sterne: 933Aktualisiert: 13. Okt. 2026
- Nr.: 7.354
Repository: alirezarezvani/claude-skills
GitHub-Sterne: 29.497Aktualisiert: 30. Okt. 2026
- Nr.: 7.355
Repository: anthropics/cwc-workshops
GitHub-Sterne: 2.285Aktualisiert: 7. Mai 2026
- Nr.: 7.356
Repository: anthropics/financial-services
GitHub-Sterne: 41.165Aktualisiert: 21. Mai 2026
- Nr.: 7.357
Repository: aresbit/claude-skills
GitHub-Sterne: 0Aktualisiert: 12. Juli 2026
- Nr.: 7.358
firstprinciplesPhysics-based reasoning framework (Musk methodology) that deconstructs a problem to irreducible fundamental truths, classifies every element as hard constraint, soft constraint, or assumption, then reconstructs the optimal solution from fundamentals alone. USE WHEN first principles, fundamental truths, challenge assumptions, real constraint, rebuild from scratch, start over, physics first, question everything, reasoning by analogy. NOT FOR structural feedback loops (use SystemsThinking).Sprache des Skill-Inhalts: Englisch
Repository: danielmiessler/LifeOS
GitHub-Sterne: 19.770Aktualisiert: 27. Okt. 2026
- Nr.: 7.359
Repository: ECNU-ICALK/AutoSkill
GitHub-Sterne: 610Aktualisiert: 16. März 2026
- Nr.: 7.360
Repository: FastLED/FastLED
GitHub-Sterne: 7.528Aktualisiert: 27. März 2026
- Nr.: 7.361
Repository: googleworkspace/cli
GitHub-Sterne: 32.198Aktualisiert: 31. März 2026
- Nr.: 7.362
Repository: LeoYeAI/openclaw-master-skills
GitHub-Sterne: 2.169Aktualisiert: 4. Mai 2026
- Nr.: 7.363
Repository: lobehub/lobehub
GitHub-Sterne: 84.502Aktualisiert: 26. Sept. 2026
- Nr.: 7.364
Repository: MGdaasLab/WHartTest
GitHub-Sterne: 1.078Aktualisiert: 23. Okt. 2026
- Nr.: 7.365
Repository: modu-ai/cowork-plugins
GitHub-Sterne: 267Aktualisiert: 19. Juni 2026
- Nr.: 7.366
Repository: nexu-io/open-design
GitHub-Sterne: 106.688Aktualisiert: 18. Aug. 2026
- Nr.: 7.367
Repository: OpenSenseNova/SenseNova-Skills
GitHub-Sterne: 6.054Aktualisiert: 26. Apr. 2026
- Nr.: 7.368
Repository: paperclipai/paperclip
GitHub-Sterne: 112.381Aktualisiert: 10. Juli 2026
- Nr.: 7.369
Repository: swaylq/master-skill
GitHub-Sterne: 174Aktualisiert: 16. Aug. 2026
- Nr.: 7.370
literature-verifierVerify the authenticity of literature references and detect hallucinations in both English and Chinese (中文) sources. Use when users need to check if a citation is real, verify a DOI, confirm a paper/article/book exists, cross-check author-title-journal-year metadata, detect fabricated references, validate URLs of online articles, or audit a reference list for accuracy. Covers journal papers, conference papers, preprints, books, monographs, newspaper articles, magazine articles, web articles, dissertations, government documents, and any other published works. Supports Chinese academic databases including CNKI (知网), Wanfang (万方), CQVIP (维普), Baidu Scholar (百度学术), and core journal list verification (北大核心, CSSCI, CSCD).Sprache des Skill-Inhalts: Mehrsprachig
Repository: yipng05-max/-skills
GitHub-Sterne: 320Aktualisiert: 30. März 2026
- Nr.: 7.371
Repository: 91zgaoge/StoryMoss
GitHub-Sterne: 78Aktualisiert: 11. Juli 2026
- Nr.: 7.372
Repository: a5c-ai/babysitter
GitHub-Sterne: 1.891Aktualisiert: 1. Juni 2026
- Nr.: 7.373
Repository: affaan-m/ECC
GitHub-Sterne: 299.529Aktualisiert: 17. Mai 2026
- Nr.: 7.374
Repository: affaan-m/ECC
GitHub-Sterne: 299.529Aktualisiert: 10. März 2026
- Nr.: 7.375
Repository: affaan-m/ECC
GitHub-Sterne: 299.529Aktualisiert: 13. März 2026
- Nr.: 7.376
bomBOM (Bill of Materials) management for electronics projects — the workflow skill that coordinates DigiKey, Mouser, LCSC, element14, JLCPCB, PCBWay, and KiCad skills around a unified BOM lifecycle. Create, update, and maintain BOMs with part numbers, costs, quantities stored as KiCad symbol properties. ALWAYS trigger this skill for any task involving component sourcing, pricing, ordering, distributor searches, BOM export, or fabrication preparation — even if the user names a specific distributor or fab house (e.g. "search DigiKey for...", "generate JLCPCB BOM", "order from Mouser"). This skill analyzes the schematic for sourcing gaps, recommends which distributor/fab skills to call for each gap, and writes results back as symbol properties — the agent (or user) performs the actual searches via the called skills. Also trigger on phrases like "what parts do I need", "order components", "how much will this cost", "export for JLCPCB", "find parts for this board", "compare pricing", or "check stock".Sprache des Skill-Inhalts: Englisch
Repository: aklofas/kicad-happy
GitHub-Sterne: 1.625Aktualisiert: 6. Nov. 2026
- Nr.: 7.377
Repository: alirezarezvani/claude-skills
GitHub-Sterne: 29.497Aktualisiert: 3. Nov. 2026
- Nr.: 7.378
Repository: anthropics/claude-plugins-official
GitHub-Sterne: 46.514Aktualisiert: 8. Okt. 2026
- Nr.: 7.379
Repository: Besty0728/Unity-Skills
GitHub-Sterne: 1.929Aktualisiert: 26. Sept. 2026
- Nr.: 7.380
Repository: caishengold/ai-agent-ops
GitHub-Sterne: 5Aktualisiert: 10. Feb. 2026
- Nr.: 7.381
hyperframes-cliHyperFrames CLI dev loop. Use when running npx hyperframes init, add, catalog, capture, lint, validate, inspect, layout, snapshot, preview, play, render, publish, lambda, doctor, browser, info, upgrade, skills, compositions, docs, benchmark, telemetry, transcribe, tts, or remove-background, or when troubleshooting the HyperFrames build/render environment. Entry point for AWS Lambda cloud rendering (`hyperframes lambda deploy / render / progress / destroy / policies`).Sprache des Skill-Inhalts: Englisch
Repository: OpenMontageInc/OpenMontage
GitHub-Sterne: 78.816Aktualisiert: 27. Juni 2026
- Nr.: 7.382
culture-fragment-poster-engineConvert fragmented cultural visual materials into traceable asset indexes, visual genes, high-end brand visual systems, poster concepts, image-generation prompts, and refined poster/KV/ad/cover layout directions. Use when the user asks to organize folders of cultural images, photography, traditional art, objects, scripts, patterns, intangible heritage, commercial reinterpretations, layout references, or to generate modern, restrained, premium cultural posters, luxury brand KVs, fashion/beauty/fragrance campaigns, ads, exhibition visuals, booklet covers, or social-media vertical visuals from those materials.Sprache des Skill-Inhalts: Englisch
Repository: dacnay816y62-hub/culture-fragment-poster-engine
GitHub-Sterne: 271Aktualisiert: 5. Sept. 2026
- Nr.: 7.383
Repository: digoal/blog
GitHub-Sterne: 8.603Aktualisiert: 8. Juni 2026
- Nr.: 7.384
Repository: Egonex-AI/Understand-Anything
GitHub-Sterne: 91.602Aktualisiert: 17. Juli 2026
- Nr.: 7.385
Repository: kiki348/photoshop-beta-control
GitHub-Sterne: 75Aktualisiert: 18. Mai 2026
- Nr.: 7.386
Repository: netease-youdao/LobsterAI
GitHub-Sterne: 6.175Aktualisiert: 25. März 2026
- Nr.: 7.387
Repository: RTGS2017/NagaAgent
GitHub-Sterne: 1.546Aktualisiert: 9. Feb. 2026
- Nr.: 7.388
social-sellingWhen the user wants to sell through social media, optimize LinkedIn for sales, build DM sequences, or convert content engagement into pipeline. Also use when the user mentions 'social selling,' 'LinkedIn selling,' 'LinkedIn DMs,' 'social prospecting,' 'LinkedIn Sales Navigator,' 'DM sequences,' 'LinkedIn outreach,' 'social pipeline,' or 'LinkedIn optimization.' This skill covers social selling strategy from profile optimization through DM-to-deal conversion. Do NOT use for technical implementation, code review, or software architecture.Sprache des Skill-Inhalts: Englisch
Repository: tech-leads-club/agent-skills
GitHub-Sterne: 7.149Aktualisiert: 14. März 2026
- Nr.: 7.389
drive-motivationDesign motivation systems using Autonomy, Mastery, and Purpose (AMP) for products and teams. Use when the user mentions "intrinsic motivation", "gamification isnt working", "rewards arent working", "autonomy", "mastery", "purpose-driven", "my team is disengaged", or "how do I motivate people". Also trigger when designing onboarding progression, fixing broken gamification, or building team structures that sustain high performance. Covers why carrot-and-stick fails and how to build progress systems. For habit-forming product loops, see hooked-ux. For retention behavior design, see improve-retention.Sprache des Skill-Inhalts: Englisch
Repository: wondelai/skills
GitHub-Sterne: 2.643Aktualisiert: 30. Juni 2026
- Nr.: 7.390
ml-causalEconometrics skill for machine learning methods in causal inference. Activates when the user asks about:
"causal forest", "generalized random forest", "GRF", "double machine learning", "DML",
"debiased machine learning", "LASSO for variable selection", "post-LASSO",
"heterogeneous treatment effects", "CATE", "conditional average treatment effect",
"BLP analysis", "CLAN analysis", "causal tree", "honest estimation",
"因果森林", "双重机器学习", "异质性处理效应", "条件平均处理效应",
"LASSO变量选择", "机器学习因果推断", "去偏机器学习"Sprache des Skill-Inhalts: Englisch
Repository: zhouziyue233/great-econometrics
GitHub-Sterne: 8Aktualisiert: 3. Apr. 2026
- Nr.: 7.391
Repository: affaan-m/ECC
GitHub-Sterne: 299.529Aktualisiert: 30. März 2026
- Nr.: 7.392
instagram-profile-metaFetches Instagram user profile metadata including bio, follower count, following count, post count, verification status and other profile details. Use when user mentions Instagram profile info, user stats, account details, follower count, bio scraping, Instagram user data, IG profile, check Instagram account, Instagram user info, how many followers does someone have on Instagram, get Instagram profile, Instagram account metadata.Sprache des Skill-Inhalts: Englisch
Repository: browser-act/skills
GitHub-Sterne: 6.339Aktualisiert: 25. Mai 2026
- Nr.: 7.393
Repository: code-yeongyu/oh-my-openagent
GitHub-Sterne: 70.793Aktualisiert: 6. Nov. 2026
- Nr.: 7.394
Repository: GoogleCloudPlatform/generative-ai
GitHub-Sterne: 17.854Aktualisiert: 15. Juli 2026
- Nr.: 7.395
Repository: luongnv89/claude-howto
GitHub-Sterne: 46.759Aktualisiert: 4. Aug. 2026
- Nr.: 7.396
Repository: meitu/meitu-skills
GitHub-Sterne: 35Aktualisiert: 28. Aug. 2026
- Nr.: 7.397
statspai-skillUse when the user asks to run a full empirical / causal analysis in Python — by default in the style of an applied economics paper (AER / QJE / JPE / ReStud / AEJ) with DID / RD / IV / SCM / DML / matching, written-out estimating equation + identifying assumption, Table 1 / Table 2 / event-study figure / robustness gauntlet — OR in epidemiology / public health style (target-trial emulation, IPTW + g-formula + TMLE triplet, Mendelian randomization, KM/AFT survival, E-value sensitivity, STROBE/TRIPOD reporting) — OR in ML causal inference style (DML, S/T/X/R/DR meta-learners, causal forest, Dragonnet/TARNet/CEVAE, BCF, CATE distribution, policy learning, conformal causal, fairness audit, causal discovery) — OR in distributional / gap-decomposition style (Oaxaca–Blinder `sp.oaxaca`, Kitagawa `sp.kitagawa_decompose`, DiNardo–Fortin–Lemieux `sp.dfl_decompose`, Gelbach `sp.gelbach`, Fairlie `sp.fairlie`, RIF / FFL `sp.rif_decomposition`, all reachable through the `sp.decompose` dispatcher). Also covers exporting muSprache des Skill-Inhalts: Englisch
Repository: brycewang-stanford/Auto-Empirical-Research-Skills
GitHub-Sterne: 4.955Aktualisiert: 15. Okt. 2026
- Nr.: 7.398
Repository: BuilderIO/agent-native
GitHub-Sterne: 7.449Aktualisiert: 22. Juli 2026
- Nr.: 7.399
Repository: zLanqing/codex-claude-academic-skills
GitHub-Sterne: 5.794Aktualisiert: 14. Mai 2026
- Nr.: 7.400
Repository: redfox-data/redfox-community
GitHub-Sterne: 450Aktualisiert: 27. Aug. 2026