[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"extension-skill-sergebulaev-linkedin-hook-extractor-de":3,"guides-for-sergebulaev-linkedin-hook-extractor":530,"similar-k177tznq5zvv146tc8qsdh01cx86nseq-de":531},{"_creationTime":4,"_id":5,"children":6,"community":7,"display":9,"evaluation":15,"identity":238,"isFallback":223,"parentExtension":243,"providers":301,"relations":305,"repo":307,"tags":527,"workflow":528},1778697338445.6934,"k177tznq5zvv146tc8qsdh01cx86nseq",[],{"reviewCount":8},0,{"description":10,"installMethods":11,"name":13,"sourceUrl":14},"Reverse-engineert die Hook-Formel aus einem viralen LinkedIn-Post-URL. Gibt zurück, welche der 10 kanonischen 2026-Formeln verwendet wird (Anapher, R.I.P., Year-Pivot, Time-Anchor, Self-Proving, Odd-Money, Paid-vs-Free, Curiosity-Gap, Contrarian, Comment-Gate), warum sie funktionierte und eine leere Vorlage. Verwenden Sie dies, um aus dem Post eines Mitbewerbers zu lernen, aber nicht, um Ihren eigenen zu schreiben (verwenden Sie linkedin-post-writer).",{"claudeCode":12},"sergebulaev/linkedin-skills","linkedin-hook-extractor","https://github.com/sergebulaev/linkedin-skills",{"_creationTime":16,"_id":17,"extensionId":5,"locale":18,"result":19,"trustSignals":221,"workflow":236},1778697338445.6936,"kn78qbkk7sgrw7pbd9eenegd2h86nwqb","de",{"checks":20,"evaluatedAt":192,"extensionSummary":193,"features":194,"nonGoals":200,"promptVersionExtension":204,"promptVersionScoring":205,"purpose":206,"rationale":207,"score":208,"summary":209,"tags":210,"tier":216,"useCases":217},[21,26,29,32,36,39,43,47,50,53,57,61,64,68,71,74,77,80,83,86,90,94,98,102,106,109,112,115,119,122,125,128,132,135,138,142,146,151,154,158,161,164,167,170,174,177,180,183,186,189],{"category":22,"check":23,"severity":24,"summary":25},"Praktischer Nutzen","Relevanz des Problems","pass","Die Beschreibung gibt klar das Problem der Reverse-Engineeing von LinkedIn-Post-Hook-Formeln aus viralen Posts an und identifiziert den Zielbenutzer, der sich für die Untersuchung von Wettbewerbsstrategien interessiert.",{"category":22,"check":27,"severity":24,"summary":28},"Einzigartiges Verkaufsversprechen","Die Fähigkeit bietet ein spezifisches Wertversprechen, indem sie Hook-Formeln reverse-engineert, psychologische Einblicke liefert und Vorlagen generiert, was über die Standardfähigkeiten von LLMs für diese Aufgabe hinausgeht.",{"category":22,"check":30,"severity":24,"summary":31},"Produktionsreife","Die Fähigkeit ist produktionsreif, da sie einen klaren Arbeitsablauf beinhaltet, externe Bibliotheken zum Parsen von URLs und zum Abrufen von Daten verwendet (mit Fallbacks) und umsetzbare Ergebnisse liefert.",{"category":33,"check":34,"severity":24,"summary":35},"Umfang","Prinzip der einzigen Verantwortung","Die Fähigkeit konzentriert sich auf eine einzige, gut definierte Aufgabe: die Analyse von LinkedIn-Post-Hooks und -Formeln, ohne zu versuchen, verwandte Funktionalitäten zu implementieren.",{"category":33,"check":37,"severity":24,"summary":38},"Qualität der Beschreibung","Die angezeigte Beschreibung spiegelt die Funktionalität der Fähigkeit genau wider, einschließlich ihres Zwecks, ihrer Ausgaben und ihres beabsichtigten Gebrauchs, und rät von der Verwendung zur Content-Generierung ab.",{"category":40,"check":41,"severity":24,"summary":42},"Aufruf","Geltungsbereich von Tools","Die Fähigkeit verwendet ein einziges, gut definiertes Tool (`lib.url_parser.parse_linkedin_url`) und stützt sich auf Python-Bibliotheken zum Abrufen und Klassifizieren, was spezifische Aktionen sind.",{"category":44,"check":45,"severity":24,"summary":46},"Dokumentation","Konfigurations- & Parameterreferenz","Konfigurationsdetails wie `APIFY_TOKEN` und optionale Fallbacks werden in der Dokumentation erwähnt. Die Fähigkeit selbst scheint keine weiteren expliziten Parameter über die Eingabe-URL und mögliche Umgebungsvariablen für externe Dienste hinaus zu haben.",{"category":33,"check":48,"severity":24,"summary":49},"Tool-Benennung","Die primäre Interaktion erfolgt über den allgemeinen Prompt der Fähigkeit; interne Bibliotheksfunktionen sind beschreibend (z. B. `parse_linkedin_url`, `fetch_post`).",{"category":33,"check":51,"severity":24,"summary":52},"Minimale I/O-Oberfläche","Die Fähigkeit nimmt eine einzelne URL als Eingabe und gibt strukturierte Daten (Formel, Struktur, Gründe, Vorlage) zurück, ohne zusätzliche Ausgabefelder.",{"category":54,"check":55,"severity":24,"summary":56},"Lizenz","Lizenznutzbarkeit","Das Projekt ist unter MIT lizenziert, einer permissiven Open-Source-Lizenz, mit einer vorhandenen LICENSE-Datei.",{"category":58,"check":59,"severity":24,"summary":60},"Wartung","Aktualität von Commits","Der letzte Commit war am 11. Mai 2026, was innerhalb der letzten 90 Tage liegt.",{"category":58,"check":62,"severity":24,"summary":63},"Abhängigkeitsmanagement","Das Projekt stützt sich auf externe Python-Bibliotheken, und die README erwähnt `pip install requests python-dotenv` für die Einrichtung, was auf einen grundlegenden Ansatz für das Abhängigkeitsmanagement hinweist, der für diesen Kontext geeignet ist.",{"category":65,"check":66,"severity":24,"summary":67},"Sicherheit","Geheimnisverwaltung","Die Fähigkeit erwähnt optionale API-Tokens (`APIFY_TOKEN`, `PUBLORA_API_KEY`), die über Umgebungsvariablen oder `.env`-Dateien gehandhabt werden, was bewährte Praktiken befolgt und keine Geheimnisse preisgibt.",{"category":65,"check":69,"severity":24,"summary":70},"Injection","Die Fähigkeit konzentriert sich auf das Parsen von URLs und die Analyse von Textinhalten, ohne externen Code oder Daten auf eine Weise zu laden oder auszuführen, die anfällig für Injection-Angriffe wäre.",{"category":65,"check":72,"severity":24,"summary":73},"Transitive Lieferketten-Granaten","Die Fähigkeit verwendet interne Python-Bibliotheken und ruft optional externe APIs (Apify, Publora) auf. Diese Interaktionen sind gut definiert und beinhalten kein Abrufen und Ausführen von beliebigem Remote-Code.",{"category":65,"check":75,"severity":24,"summary":76},"Sandbox-Isolation","Die Fähigkeit arbeitet mit bereitgestellten URLs und Texten und führt Analysen durch. Sie verändert keine Dateien außerhalb ihres eigenen Geltungsbereichs oder Projektordners.",{"category":65,"check":78,"severity":24,"summary":79},"Sandbox-Escape-Primitive","Es gibt keine Anzeichen für getrennte Prozesse oder Wiederholungsversuche bei abgelehnten Tool-Aufrufen im bereitgestellten Code.",{"category":65,"check":81,"severity":24,"summary":82},"Datenexfiltration","Der Zweck der Fähigkeit ist die Analyse, nicht die Datenübermittlung. Sie liest nur Inhalte von einer bereitgestellten URL und verarbeitet diese lokal. Alle ausgehenden Aufrufe zum Datenabruf sind optional und dokumentiert.",{"category":65,"check":84,"severity":24,"summary":85},"Versteckte Texttricks","Die gebündelten Markdown- und Python-Dateien enthalten keine versteckten Texte, Unicode-Tricks oder andere Verschleierungsmethoden.",{"category":87,"check":88,"severity":24,"summary":89},"Hooks","Undurchsichtige Codeausführung","Der Python-Code ist klar und lesbar, ohne Anzeichen von Verschleierung, Base64-Payloads oder Laufzeit-Code-Abruf.",{"category":91,"check":92,"severity":24,"summary":93},"Portabilität","Strukturelle Annahme","Die Fähigkeit nimmt eine URL als Eingabe und verarbeitet sie, ohne Annahmen über die lokale Projektstruktur oder das Dateilayout des Benutzers zu treffen.",{"category":95,"check":96,"severity":24,"summary":97},"Vertrauen","Aufmerksamkeit bei Issues","Es gibt 0 offene und 0 geschlossene Issues in den letzten 90 Tagen, was auf geringe aktuelle Aktivität, aber keine Anzeichen von Vernachlässigung hindeutet.",{"category":99,"check":100,"severity":24,"summary":101},"Versionierung","Release-Management","Das Projekt deklariert ein 'release'-Tag auf GitHub mit einem aktuellen Datum, was auf eine Form der Versionierung hindeutet, obwohl ein formelles Semver im Frontmatter fehlt.",{"category":103,"check":104,"severity":24,"summary":105},"Codeausführung","Validierung","Das Skript `lib/url_parser.py` validiert URL-Formate, und die Gesamtstruktur impliziert klar definierte Ein- und Ausgaben, obwohl explizite Schema-Validierungsbibliotheken im bereitgestellten Code nicht detailliert sind.",{"category":65,"check":107,"severity":24,"summary":108},"Ungeschützte destruktive Operationen","Die Fähigkeit ist schreibgeschützt und analytisch und führt keine destruktiven Operationen durch.",{"category":103,"check":110,"severity":24,"summary":111},"Fehlerbehandlung","Die Python-Bibliotheken und die Fähigkeitsschritte scheinen Standardverfahren zur Fehlerbehandlung zu befolgen. `lib/url_parser.py` enthält grundlegende Fehlerbehandlung für ungültige URLs, und externe API-Aufrufe würden inhärent Fehlerbehandlung beinhalten.",{"category":103,"check":113,"severity":24,"summary":114},"Protokollierung","Die Fähigkeit ist primär analytisch und führt keine destruktiven Aktionen oder sensible ausgehende Aufrufe durch, die eine detaillierte Audit-Protokollierung über die standardmäßige Konsolenausgabe für Debugging hinaus erfordern würden.",{"category":116,"check":117,"severity":24,"summary":118},"Compliance","DSGVO","Die Fähigkeit analysiert öffentliche LinkedIn-Post-Daten und verarbeitet keine personenbezogenen Daten über das hinaus, was öffentlich auf einem LinkedIn-Profil verfügbar ist, ohne Weitergabe an Dritte.",{"category":116,"check":120,"severity":24,"summary":121},"Zielmarkt","Die Fähigkeit analysiert LinkedIn-Posts, die global zugänglich sind, und der Code selbst hat keine regionalen Einschränkungen, was ihn global anwendbar macht.",{"category":91,"check":123,"severity":24,"summary":124},"Laufzeitstabilität","Die Fähigkeit ist in Python geschrieben und stützt sich auf Standardbibliotheken und optional externe APIs, was sie über verschiedene Python-Umgebungen hinweg portierbar macht.",{"category":44,"check":126,"severity":24,"summary":127},"README","Die README-Datei ist umfassend und beschreibt Installation, Nutzung, verwandte Fähigkeiten und optionale Integrationen, wobei sie den Zweck der Erweiterung klar darlegt.",{"category":33,"check":129,"severity":130,"summary":131},"Tool-Oberflächengröße","not_applicable","Dies ist eine Einzweck-Fähigkeit, die über einen Prompt aufgerufen wird, keine Menge von separaten Tools mit einer zu bewertenden Oberflächengröße.",{"category":40,"check":133,"severity":24,"summary":134},"Überlappende Fast-Synonym-Tools","Die Fähigkeit führt eine einzige Hauptfunktion aus, daher gibt es keine überlappenden Fast-Synonym-Tools.",{"category":44,"check":136,"severity":24,"summary":137},"Phantom-Funktionen","Alle beworbenen Funktionen, wie URL-Parsing, Klassifizierung und Vorlagengenerierung, sind implementiert und in SKILL.md und verwandten Dateien beschrieben.",{"category":139,"check":140,"severity":24,"summary":141},"Installation","Installationsanleitung","Die README enthält klare Installationsanweisungen für verschiedene Plattformen (claude.ai, Desktop, OpenClaw, Claude Code) und beinhaltet Beispielaufrufe.",{"category":143,"check":144,"severity":24,"summary":145},"Fehler","Umsetzbare Fehlermeldungen","Das Skript `lib/url_parser.py` behandelt ungültige URLs mit spezifischen Fehlermeldungen, und das allgemeine Fähigkeitsdesign impliziert eine strukturierte Fehlerberichterstattung für API-Interaktionen.",{"category":147,"check":148,"severity":149,"summary":150},"Ausführung","Angeheftete Abhängigkeiten","info","Die README erwähnt `pip install requests python-dotenv`, aber spezifische Versionen sind nicht angeheftet, noch wird explizit eine Lock-Datei für Python-Abhängigkeiten erwähnt.",{"category":33,"check":152,"severity":24,"summary":153},"Dry-Run-Vorschau","Die Fähigkeit ist analytisch und führt keine Zustandsänderungen oder ausgehenden Datensendungen durch, wodurch ein Dry-Run-Modus nicht anwendbar ist.",{"category":155,"check":156,"severity":24,"summary":157},"Protokoll","Idempotente Wiederholung & Timeouts","Die Fähigkeit ist primär analytisch. Jegliche externen API-Aufrufe würden sich auf die Fehlerbehandlung der zugrunde liegenden Bibliothek oder API für Timeouts und Wiederholungen verlassen, und die Fähigkeit selbst führt keine zustandsverändernden Operationen durch.",{"category":116,"check":159,"severity":24,"summary":160},"Telemetrie-Opt-in","Die Fähigkeit konzentriert sich auf die Analyse und sendet standardmäßig keine Telemetriedaten. Optionale API-Nutzung (Apify, Publora) ist dokumentiert und über Umgebungsvariablen verwaltet, nicht über breite Telemetrie.",{"category":40,"check":162,"severity":24,"summary":163},"Präziser Zweck","Die Fähigkeit definiert klar ihren Zweck: Reverse-Engineeing von LinkedIn-Post-Hook-Formeln. Sie spezifiziert die Eingabe (URL), die Ausgabe (Formel, Struktur, Analyse, Vorlage) und die Anwendungsfälle (Lernen von Wettbewerbern, Anregung von Entwürfen), während sie explizit ein Nicht-Ziel (direktes Schreiben von Posts) angibt.",{"category":40,"check":165,"severity":24,"summary":166},"Prägnanter Frontmatter","Der SKILL.md-Frontmatter ist prägnant und in sich geschlossen, fasst die Kernfähigkeit zusammen und listet Trigger-Phrasen effektiv auf.",{"category":44,"check":168,"severity":24,"summary":169},"Prägnanter Body","Der SKILL.md-Body ist prägnant, beschreibt den Arbeitsablauf und verweist auf externe Dateien für detaillierte Regeln und Beispiele, wobei die progressive Offenlegung eingehalten wird.",{"category":171,"check":172,"severity":24,"summary":173},"Kontext","Progressive Offenlegung","Die SKILL.md verweist auf `references/classification-rules.md` und `references/examples.md` für detaillierte Informationen und demonstriert so die progressive Offenlegung.",{"category":171,"check":175,"severity":130,"summary":176},"Gegabelte Erkundung","Die Fähigkeit führt eine fokussierte Analyse durch und beinhaltet keine tiefgehende Erkundung oder mehrdateiliche Inspektion, die einen gegabelten Kontext erfordern würde.",{"category":22,"check":178,"severity":24,"summary":179},"Nutzungsbeispiele","Die Datei `references/examples.md` liefert ein klares Beispiel, das die Eingabe-URL, die erwartete Ausgabestruktur und die leere Vorlage zeigt, und erfüllt damit die Anforderung nach Nutzungsbeispielen.",{"category":22,"check":181,"severity":24,"summary":182},"Randfälle","Die Dateien `references/hook-formulas.md` und `skills/linkedin-hook-extractor/references/classification-rules.md` diskutieren den Umgang mit Hybrid-Hooks, reinen Erzähl-Posts und nicht-englischem Inhalt, zusammen mit Konfidenzbewertungen und der Logik zur Merkmalsextraktion, und behandeln so potenzielle Randfälle.",{"category":103,"check":184,"severity":24,"summary":185},"Tool-Fallback","Die Fähigkeit erwähnt die optionale API-Nutzung mit Fallbacks (z. B. Einfügen von Text, wenn kein Apify-Token gesetzt ist) und listet die Anforderungen in der Dokumentation auf.",{"category":65,"check":187,"severity":24,"summary":188},"Abbruch bei unerwartetem Zustand","Das Skript `lib/url_parser.py` enthält grundlegende Fehlerbehandlung für ungültige Eingaben, und das Design der Fähigkeit impliziert, dass fehlerhafte Eingaben oder API-Fehler den Prozess ordnungsgemäß abbrechen würden.",{"category":91,"check":190,"severity":24,"summary":191},"Kreuz-Skill-Kopplung","Die Fähigkeit ist in sich geschlossen und stützt sich nicht implizit auf andere Fähigkeiten. Sie verweist jedoch auf verwandte Fähigkeiten wie `linkedin-post-writer` und `linkedin-humanizer` für ergänzende Aufgaben.",1778697164294,"Diese Fähigkeit analysiert eine gegebene LinkedIn-Post-URL, um die verwendete Hook-Formel zu identifizieren, die Struktur des Posts zu analysieren, zu erklären, warum er effektiv war, und eine leere Vorlage zur Replikation bereitzustellen. Sie verwendet interne Python-Bibliotheken zum Parsen von URLs und integriert sich optional mit Apify zum Abrufen von Post-Inhalten, mit Fallbacks für die manuelle Eingabe. Die Analyse umfasst 10 kanonische Hook-Formeln und kennzeichnet potenzielle KI-Hinweise im Original-Post.",[195,196,197,198,199],"Reverse-Engineeing von Hook-Formeln aus LinkedIn-Posts","Identifizierung von 10 kanonischen 2026-Hook-Formeln","Analyse der Post-Struktur und psychologischen Effektivität","Generierung einer leeren Vorlage, die auf das Thema des Posts abgestimmt ist","Prüfung von Original-Posts auf KI-Hinweise und veraltete Taktiken",[201,202,203],"Direktes Schreiben neuer LinkedIn-Posts (verwenden Sie stattdessen `linkedin-post-writer`)","Analyse von Posts, die nicht viral oder öffentlich zugänglich sind","Bereitstellung von Echtzeit-LinkedIn-Engagement-Metriken","3.0.0","4.4.0","Um Benutzern zu helfen, die zugrunde liegende Struktur und die psychologischen Treiber von viralen LinkedIn-Posts zu verstehen, damit sie aus erfolgreichen Inhalten lernen und ihre eigene Content-Strategie informieren können.","Die Fähigkeit ist hochgradig poliert, mit ausgezeichneter Dokumentation, klarem Umfang und robuster Implementierung. 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a LinkedIn comment on someone else's post from its URL. Use when the user pastes a post URL and asks to comment, engage, or be first commenter. Produces 1-3 variants in the user's voice, picks a reaction, and schedules via Publora on approval. Not for replying to existing comments (use linkedin-reply-handler).","linkedin-comment-drafter",{"claudeCode":12},"SKILL.md frontmatter at skills/linkedin-comment-drafter/SKILL.md",[362,364,366,368],{"path":363,"priority":319},"SKILL.md",{"path":365,"priority":336},"references/comment-templates.md",{"path":367,"priority":336},"references/examples.md",{"path":369,"priority":336},"references/voice-rules.md",{"basePath":371,"description":372,"displayName":373,"installMethods":374,"rationale":375,"selectedPaths":376,"source":325,"sourceLanguage":253,"type":242},"skills/linkedin-content-planner","Generate a 7-day LinkedIn content plan from a theme, audience, and pillars. Produces per-day post pillar, format, hook type, CTA, posting time, daily comment targets, and a weekly inbound-readiness check. Use when the user wants to plan a week or month of content, not draft a single post.","linkedin-content-planner",{"claudeCode":12},"SKILL.md frontmatter at skills/linkedin-content-planner/SKILL.md",[377,378,380],{"path":363,"priority":319},{"path":379,"priority":336},"references/example-plan-week.md",{"path":381,"priority":336},"references/pillars-framework.md",{"basePath":383,"description":384,"displayName":385,"installMethods":386,"rationale":387,"selectedPaths":388,"source":325,"sourceLanguage":253,"type":242},"skills/linkedin-employee-advocacy","Stand up and run a LinkedIn employee advocacy program for a marketing or sales team. Covers 14-day launch playbook, brand-guideline governance, per-post time budget, cadence benchmarks, and team ROI (reach, engagement, pipeline). Triggers on \"employee advocacy\", \"get the team posting\", \"scale LinkedIn across team\", \"advocacy ROI\".","linkedin-employee-advocacy",{"claudeCode":12},"SKILL.md frontmatter at skills/linkedin-employee-advocacy/SKILL.md",[389,390,392,394],{"path":363,"priority":319},{"path":391,"priority":336},"references/advocacy-principles.md",{"path":393,"priority":336},"references/governance-playbook.md",{"path":395,"priority":336},"references/team-cadence-matrix.md",{"basePath":397,"description":398,"displayName":399,"installMethods":400,"rationale":401,"selectedPaths":402,"source":325,"sourceLanguage":253,"type":242},"skills/linkedin-engager-analytics","Pull the people who liked or commented on any LinkedIn post and segment them by ICP fit (peer / aspirational / prospect / other). Produces an engager roster, tier breakdown, and outbound action lists (follow back, comment-drop, DM-able with one-line openers). Powered by Apify, no LinkedIn login. Triggers on \"who liked my post\", \"who engaged\", \"engagers report\", \"audience analytics\". Not for tracking author replies to your comments (use linkedin-thread-monitor).","linkedin-engager-analytics",{"claudeCode":12},"SKILL.md frontmatter at skills/linkedin-engager-analytics/SKILL.md",[403,404],{"path":363,"priority":319},{"path":405,"priority":336},"references/output-spec.md",{"basePath":239,"description":407,"displayName":13,"installMethods":408,"rationale":409,"selectedPaths":410,"source":325,"sourceLanguage":253,"type":242},"Reverse-engineer the hook formula from a viral LinkedIn post URL. Returns which of the 10 canonical 2026 formulas it uses (anaphora, R.I.P., year-pivot, time-anchor, self-proving, odd-money, paid-vs-free, curiosity-gap, contrarian, comment-gate), why it worked, and a blank template. Use to learn from a competitor's post, not to write your own (use linkedin-post-writer).",{"claudeCode":12},"SKILL.md frontmatter at skills/linkedin-hook-extractor/SKILL.md",[411,412,414],{"path":363,"priority":319},{"path":413,"priority":336},"references/classification-rules.md",{"path":367,"priority":336},{"basePath":416,"description":417,"displayName":418,"installMethods":419,"rationale":420,"selectedPaths":421,"source":325,"sourceLanguage":253,"type":242},"skills/linkedin-humanizer","Scrub AI tells from any text draft OR audit a finished post against the 2026 algorithm heuristic checklist. Tier-based rewriter (forensic / strict / aesthetic / all) plus `--mode audit` for detection-only pass-fail review covering length, hook, CTA, format penalties, AI vocab. Sub-tools: emoji-pattern detector, multi-detector spread tester (GPTZero, Originality.ai, ZeroGPT, Sapling, Copyleaks), rule explainer. Triggers on \"humanize\", \"de-AI\", \"review this draft\", \"audit before posting\", \"is this ready\".","linkedin-humanizer",{"claudeCode":12},"SKILL.md frontmatter at skills/linkedin-humanizer/SKILL.md",[422,423,425,427,429,431,433,434,436,438,440,442,445,447],{"path":363,"priority":319},{"path":424,"priority":336},"references/audit-ai-tells.md",{"path":426,"priority":336},"references/audit-checklist.md",{"path":428,"priority":336},"references/audit-examples.md",{"path":430,"priority":336},"references/detector-list.md",{"path":432,"priority":336},"references/emoji-patterns.md",{"path":367,"priority":336},{"path":435,"priority":336},"references/rules-explainer.md",{"path":437,"priority":336},"references/scrub-rules.md",{"path":439,"priority":336},"references/tier-rationale.md",{"path":441,"priority":336},"references/voice-fingerprint.md",{"path":443,"priority":444},"scripts/detectors.env.example","low",{"path":446,"priority":444},"scripts/requirements.txt",{"path":448,"priority":444},"scripts/test_detectors.py",{"basePath":450,"description":451,"displayName":452,"installMethods":453,"rationale":454,"selectedPaths":455,"source":325,"sourceLanguage":253,"type":242},"skills/linkedin-post-writer","Draft a new LinkedIn post from scratch using a 2026 hook formula (anaphora, R.I.P., year-pivot, time-anchor, self-proving, paid-vs-free, curiosity-gap, odd-money, contrarian). Runs the humanizer pass and schedules via Publora on approval. Use when the user asks to write a post, needs a hook, or wants a proven format. Not for reviewing existing drafts (use linkedin-humanizer --mode audit).","linkedin-post-writer",{"claudeCode":12},"SKILL.md frontmatter at skills/linkedin-post-writer/SKILL.md",[456,457,459,461],{"path":363,"priority":319},{"path":458,"priority":336},"references/algorithm-heuristics.md",{"path":460,"priority":336},"references/hook-formulas.md",{"path":462,"priority":336},"references/humanizer-checklist.md",{"basePath":464,"description":465,"displayName":466,"installMethods":467,"rationale":468,"selectedPaths":469,"source":325,"sourceLanguage":253,"type":242},"skills/linkedin-profile-optimizer","Audit and rewrite a LinkedIn profile end-to-end for 2026: headline, About 7-step, Featured, banner, photo, Experience metrics, Skills, custom URL, recommendations. Triggers on \"review my profile\", \"rewrite my headline\", \"fix my About\", \"optimize banner\", \"profile audit\", \"LinkedIn bio\". Converts resume-style profiles to ones that convert 3-5x better.","linkedin-profile-optimizer",{"claudeCode":12},"SKILL.md frontmatter at skills/linkedin-profile-optimizer/SKILL.md",[470,471,473,475,477,479],{"path":363,"priority":319},{"path":472,"priority":336},"references/about-section-templates.md",{"path":474,"priority":336},"references/banner-photo-specs.md",{"path":476,"priority":336},"references/experience-skills-rules.md",{"path":478,"priority":336},"references/featured-section-playbook.md",{"path":480,"priority":336},"references/profile-headline-formulas.md",{"basePath":482,"description":483,"displayName":484,"installMethods":485,"rationale":486,"selectedPaths":487,"source":325,"sourceLanguage":253,"type":242},"skills/linkedin-reply-handler","Draft a reply to a specific existing LinkedIn comment from its URL. Use when the user wants to reply to a comment on any post, or follow up after an author replied to them. Parses the commentUrn, resolves the correct parentComment target (LinkedIn flattens threads to 2 levels), and posts via Publora on approval. Not for top-level comments (use linkedin-comment-drafter).","linkedin-reply-handler",{"claudeCode":12},"SKILL.md frontmatter at skills/linkedin-reply-handler/SKILL.md",[488,489,490,492],{"path":363,"priority":319},{"path":367,"priority":336},{"path":491,"priority":336},"references/reply-templates.md",{"path":493,"priority":336},"references/threading-rules.md",{"basePath":495,"description":496,"displayName":497,"installMethods":498,"rationale":499,"selectedPaths":500,"source":325,"sourceLanguage":253,"type":242},"skills/linkedin-thread-monitor","Track which of your LinkedIn comments earned author replies. Flags the 6-24h Kevin Payne window where thread momentum peaks, classifies threads as hot/warm/cool/dormant, and routes warm ones to linkedin-reply-handler for follow-up drafts. Powered by Apify, no LinkedIn login. Triggers on \"what threads need follow-up\", \"author replied\", \"monitor my comments\". Not for analyzing likers on a post (use linkedin-engager-analytics).","linkedin-thread-monitor",{"claudeCode":12},"SKILL.md frontmatter at skills/linkedin-thread-monitor/SKILL.md",[501,502,503],{"path":363,"priority":319},{"path":405,"priority":336},{"path":504,"priority":336},"references/thread-timing.md",{"sources":506},[507],"manual",{"closedIssues90d":8,"description":509,"forks":229,"homepage":14,"license":233,"openIssues90d":8,"pushedAt":230,"readmeSize":227,"stars":231,"topics":510},"Claude Code skills for LinkedIn growth: write human-sounding posts, craft comments that get noticed, analyze your feed, and build a publishing cadence — all from your terminal. Plug-and-play skills for content creators, founders, and marketers using Claude Code.",[272,511,512,513,514,515,516,269,211,517,518,519,520,521,522],"ai-content","ai-marketing","anthropic","awesome-claude","claude-code","claude-skills","linkedin-automation","llm-tools","mcp","personal-branding","prompt-engineering","social-media-automation",{"classifiedAt":524,"discoverAt":525,"extractAt":526,"githubAt":526,"updatedAt":524},1778697044829,1778697040628,1778697042787,[213,215,211,212,214],{"evaluatedAt":529,"extractAt":286,"updatedAt":237},1778697164405,[],[532,564,593,616,645,667],{"_creationTime":533,"_id":534,"community":535,"display":536,"identity":542,"providers":546,"relations":557,"tags":560,"workflow":561},1778675056600.264,"k17169sg21srwv5sf3enw3dgcd86m4sh",{"reviewCount":8},{"description":537,"installMethods":538,"name":540,"sourceUrl":541},"When the user wants help creating, scheduling, or optimizing social media content for LinkedIn, Twitter/X, Instagram, TikTok, Facebook, or other platforms. Also use when the user mentions 'LinkedIn post,' 'Twitter thread,' 'social media,' 'content calendar,' 'social scheduling,' 'engagement,' or 'viral content.' This skill covers content creation, repurposing, and platform-specific strategies.",{"claudeCode":539},"alirezarezvani/claude-skills","Social Content","https://github.com/alirezarezvani/claude-skills",{"basePath":543,"githubOwner":544,"githubRepo":516,"locale":253,"slug":545,"type":242},"marketing-skill/skills/social-content","alirezarezvani","social-content",{"evaluate":547,"extract":556},{"promptVersionExtension":204,"promptVersionScoring":205,"score":548,"tags":549,"targetMarket":273,"tier":216},100,[212,270,269,550,551,552,211,553,554,555],"content-strategy","scheduling","twitter","instagram","tiktok","facebook",{"commitSha":276,"license":233},{"parentExtensionId":558,"repoId":559},"k170sws65f0ebecn36z3q8c2z186m477","kd7ff9s1w43mfyy1n7hf87816186m6px",[269,550,555,553,211,212,551,270,554,552],{"evaluatedAt":562,"extractAt":563,"updatedAt":562},1778685179349,1778675056600,{"_creationTime":565,"_id":566,"community":567,"display":568,"identity":574,"providers":578,"relations":586,"tags":589,"workflow":590},1778696595410.5671,"k17anj41t8hgk7k78wc98gw6a186n8ks",{"reviewCount":8},{"description":569,"installMethods":570,"name":572,"sourceUrl":573},"Prevent destructive operations using Claude Code hooks. Three modes — cautious (warn on dangerous commands), lockdown (restrict edits to one directory), and clear (remove restrictions). Uses PreToolUse matchers for Bash, Edit, and Write.",{"claudeCode":571},"rohitg00/pro-workflow","safe-mode","https://github.com/rohitg00/pro-workflow",{"basePath":575,"githubOwner":576,"githubRepo":577,"locale":253,"slug":572,"type":242},"skills/safe-mode","rohitg00","pro-workflow",{"evaluate":579,"extract":585},{"promptVersionExtension":204,"promptVersionScoring":205,"score":548,"tags":580,"targetMarket":273,"tier":216},[581,582,583,584,215],"security","guardrails","operations","code-quality",{"commitSha":276},{"parentExtensionId":587,"repoId":588},"k17fxtjcfh5gvxdrhv2dmgn1t986mdhv","kd7am4e918eq98hrd9s31jm4vs86nn0b",[584,582,215,583,581],{"evaluatedAt":591,"extractAt":592,"updatedAt":591},1778696971063,1778696595410,{"_creationTime":594,"_id":595,"community":596,"display":597,"identity":601,"providers":602,"relations":610,"tags":612,"workflow":613},1778697340578.6748,"k17081s5z94tqm394g1gx2b11h86m8nx",{"reviewCount":8},{"description":598,"installMethods":599,"name":600,"sourceUrl":14},"Schrubbt KI-Anzeichen aus jedem Textentwurf ODER prüft einen fertigen Beitrag anhand der Checkliste für heuristische Algorithmen von 2026. Umschreiber auf mehreren Ebenen (forensisch / streng / ästhetisch / alle) plus `--mode audit` für eine reine Erkennungsprüfung mit Bestehen/Nichtbestehen-Bewertung, die Länge, Aufhänger, Handlungsaufforderung, Formatstrafen und KI-Vokabular abdeckt. Unterwerkzeuge: Emoji-Mustererkennung, Tester für die Verteilung mehrerer Detektoren (GPTZero, Originality.ai, ZeroGPT, Sapling, Copyleaks), Regelerklärer. Löst bei \"humanisieren\", \"de-KI\", \"diesen Entwurf prüfen\", \"vor dem Posten prüfen\", \"ist das fertig\" aus.",{"claudeCode":12},"LinkedIn Humanizer",{"basePath":416,"githubOwner":240,"githubRepo":241,"locale":18,"slug":418,"type":242},{"evaluate":603,"extract":609},{"promptVersionExtension":204,"promptVersionScoring":205,"score":548,"tags":604,"targetMarket":273,"tier":216},[605,606,211,607,608],"ai-detection","text-rewriting","content-generation","nlp",{"commitSha":276,"license":233},{"parentExtensionId":245,"repoId":282,"translatedFrom":611},"k1709qff277g3qreq668nrfj0d86nrrb",[605,607,211,608,606],{"evaluatedAt":614,"extractAt":286,"updatedAt":615},1778697181923,1778697340578,{"_creationTime":617,"_id":618,"community":619,"display":620,"identity":626,"providers":629,"relations":638,"tags":641,"workflow":642},1778698867338.3027,"k171kgm311805z9fa64vzfgkqs86nb64",{"reviewCount":8},{"description":621,"installMethods":622,"name":624,"sourceUrl":625},"Clarify brand messaging using narrative structure that positions the customer as hero. Use when the user mentions \"brand message\", \"website copy\", \"elevator pitch\", \"one-liner\", \"messaging isnt resonating\", \"brand script\", \"StoryBrand framework\", or \"customer as hero\". Also trigger when rewriting homepage copy, crafting email nurture sequences, or creating consistent messaging across sales collateral and marketing materials. Covers landing page copy, marketing collateral, and consistent communication. For memorable messaging, see made-to-stick. For product positioning, see obviously-awesome.",{"claudeCode":623},"wondelai/skills","storybrand-messaging","https://github.com/wondelai/skills",{"basePath":624,"githubOwner":627,"githubRepo":628,"locale":253,"slug":624,"type":242},"wondelai","skills",{"evaluate":630,"extract":637},{"promptVersionExtension":204,"promptVersionScoring":205,"score":548,"tags":631,"targetMarket":273,"tier":216},[212,632,633,634,635,636],"messaging","branding","storytelling","copywriting","sales",{"commitSha":276},{"parentExtensionId":639,"repoId":640},"k17bj16z8e1yp2wwfd2hxagjtd86m0fp","kd7aexggvp8qjwjtgjbetg0jch86mg5a",[633,635,212,632,636,634],{"evaluatedAt":643,"extractAt":644,"updatedAt":643},1778699553427,1778698867338,{"_creationTime":646,"_id":647,"community":648,"display":649,"identity":653,"providers":655,"relations":663,"tags":664,"workflow":665},1778698867338.298,"k17eany15hcz465k5n1zhc55cd86nzs2",{"reviewCount":8},{"description":650,"installMethods":651,"name":652,"sourceUrl":625},"Apply the six principles of ethical persuasion (reciprocity, commitment, social proof, authority, liking, scarcity) to product design, copy, and sales. Use when the user mentions \"social proof\", \"persuasive copy\", \"why users dont convert\", \"ethical persuasion\", \"reciprocity\", \"scarcity tactics\", or \"commitment and consistency\". Also trigger when designing testimonial sections, crafting urgency messaging, or improving trust signals on landing pages. For deal negotiation tactics, see negotiation. For viral word-of-mouth, see contagious.",{"claudeCode":623},"Influence Psychology",{"basePath":654,"githubOwner":627,"githubRepo":628,"locale":253,"slug":654,"type":242},"influence-psychology",{"evaluate":656,"extract":662},{"promptVersionExtension":204,"promptVersionScoring":205,"score":548,"tags":657,"targetMarket":273,"tier":216},[212,635,658,659,660,661,636],"product-design","psychology","persuasion","ux",{"commitSha":276,"license":233},{"parentExtensionId":639,"repoId":640},[635,212,660,658,659,636,661],{"evaluatedAt":666,"extractAt":644,"updatedAt":666},1778699285462,{"_creationTime":668,"_id":669,"community":670,"display":671,"identity":677,"providers":681,"relations":689,"tags":691,"workflow":692},1778696113180.8118,"k17b8dp19k5ecqjt52xcm30vvn86nbsx",{"reviewCount":8},{"description":672,"installMethods":673,"name":675,"sourceUrl":676},"Cross-format content adaptation. Turning one substantial piece into many derivative formats (blog series, email sequences, social posts, webinars, podcasts, video shorts) without losing the original's value or producing AI-slop variants. The discipline of adaptation per medium rather than mass-blast distribution. Triggers on content repurposing, content adaptation, cross-format content, content atomization, content multiplication, content distribution across formats, source-piece-to-derivative, video shorts from blog, email from whitepaper, podcast from article, blog series from research. Also triggers when a flagship piece is shipping but the team has not planned how to extend it across formats, when repurposing is happening but the derivatives feel mass-produced, or when AI-assisted repurposing is producing slop variants of strong source pieces.",{"claudeCode":674},"rampstackco/claude-skills","Content Repurposing","https://github.com/rampstackco/claude-skills",{"basePath":678,"githubOwner":679,"githubRepo":516,"locale":253,"slug":680,"type":242},"skills/content-repurposing","rampstackco","content-repurposing",{"evaluate":682,"extract":688},{"promptVersionExtension":204,"promptVersionScoring":205,"score":548,"tags":683,"targetMarket":273,"tier":216},[550,684,212,685,686,687],"repurposing","seo","documentation","editorial",{"commitSha":276,"license":233},{"repoId":690},"kd7bebccrrd1xf6w868aggftrd86m86v",[550,686,687,212,684,685],{"evaluatedAt":693,"extractAt":694,"updatedAt":693},1778696593545,1778696113180]