「bots」の検索結果

Belastbaren Produktmarketing-Kontext für Positionierung, Zielgruppen, Botschaften, Einwände und Nachweise erstellen, prüfen und aktualisieren. Nutze diesen Skill, wenn die gemeinsame Grundlage fehlt, auf die sich Texte, Content, Vergleiche und Kampagnen stützen sollen: ICP, Jobs-to-be-Done, Nutzenversprechen, Differenzierung, Preislogik, Einwandbehandlung und Belegklassen. Legt das Ergebnis als `.agents/product-marketing.md` im Projekt ab und kennzeichnet, was belegt, was Anbieterangabe und was Annahme ist. Ersetzt weder Kundenforschung noch Rechtsprüfung.

日本語の概要は準備中です。原文の説明を表示しています。

Sichtbarkeit, Zitierung und Empfehlung in KI-Antwortsystemen für Deutschland und den DACH-Raum evidenzbasiert prüfen und verbessern. Nutze diesen Skill, wenn eine Marke oder Seite in KI-Overviews, ChatGPT, Perplexity, Gemini oder Copilot auftauchen soll, wenn Crawler-Freigaben für KI-Bots, llms.txt, strukturierte Daten oder die Extrahierbarkeit von Inhalten zu bewerten sind, oder wenn jemand nach AEO, GEO oder LLMO fragt. Trennt Abruf, Zitierung, Erwähnung und Empfehlung, prüft Behauptungen über KI-Rankingfaktoren gegen Primärquellen und verspricht keine Sichtbarkeit. Für klassisches technisches SEO ist seo-audit zuständig.

日本語の概要は準備中です。原文の説明を表示しています。

Create high-quality, model-aware system prompts for any LLM (Claude, GPT, Gemini, open-source, etc.). Use this skill whenever the user wants to create, write, build, design, draft, or improve a system prompt, system instructions, or custom instructions for any AI model. Also trigger when the user asks about prompt engineering, prompt design, prompt optimization, or wants to define behavior for an AI assistant, chatbot, agent, or any LLM-powered application — even if they don't explicitly say "system prompt". Covers all use cases including chatbots, agentic systems, tool-use workflows, content generation, data extraction, code assistants, and multi-turn conversations.

日本語の概要は準備中です。原文の説明を表示しています。

Audits fielded survey-response data for registered elements, data quality, bot and AI-automation screening, and sample integrity, and produces an appendix-ready quality report. Use at soft launch before full field, after fielding before outcomes are analyzed, or when asked what a study did about bots and AI respondents.

日本語の概要は準備中です。原文の説明を表示しています。

Map how customers discover, evaluate, and choose a product across Google, AI chatbots (ChatGPT, Claude, Perplexity), and social platforms, using the 5-stage awareness journey. Use when the user asks about search intent, AI SEO prompts, discoverability, buyer journeys, awareness stages, or what content to create for a brand, website, or keyword list.

日本語の概要は準備中です。原文の説明を表示しています。

Use whenever the user wants to find, shortlist, vet, or enrich US AI/ML/data consulting firms (consultancies) — AI/ML development, MLOps, generative AI / LLM apps (RAG, chatbots, agents), computer vision, NLP, recommendation systems, data engineering, BI/analytics. Triggers on "find an AI/ML consulting firm to build our recommendation engine", "shortlist three RAG/LLM consultancies for an enterprise chatbot", "compare three AI/ML consulting firms with strong ratings", or "pull contact info for these 8 AI consultancy domains", even when described indirectly (we want to use AI for X, deploy ML to production). Drives the ServiceGraph API (api.servicegraph.co) — a 100k+ US firm catalog filterable by industry, services, location, size, ratings. Defer to find-software-developer for general app/backend work where AI is just a feature. Skip in-house ML/data hires, LLM/AI-tool comparisons (ChatGPT vs Claude), "how do I fine-tune X" DIY questions, AI courses for individuals, non-US firms, individual freelancers.

日本語の概要は準備中です。原文の説明を表示しています。

AI Engine is a WordPress plugin by Meow Apps that connects sites to OpenAI, Claude, Gemini, and other models while exposing WordPress actions through MCP and REST interfaces. This skill helps agents configure providers, enable the plugin's MCP capabilities, and automate content, chatbots, media, and site-management workflows from WordPress.

日本語の概要は準備中です。原文の説明を表示しています。

Nature-style engineering manuscript reviewer skill for testing devices, robots, platforms, systems, algorithms embodied in physical systems and engineering methods against requirements, validation, benchmarking, uncertainty, robustness and failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

Expert-level Slack platform development using Bolt SDK — build Slack apps with slash commands, interactive components (buttons, modals, shortcuts), home tabs, event subscriptions, workflows, Socket Mode, and Block Kit. Use for building Slack bots, workflow automation, and rich interactive Slack experiences.

日本語の概要は準備中です。原文の説明を表示しています。

Technical SEO audit across 9 categories: crawlability, indexability, security, URL structure, mobile, Core Web Vitals, structured data, JavaScript rendering, and IndexNow protocol. Use when user says "technical SEO", "crawl issues", "robots.txt", "Core Web Vitals", "site speed", or "security headers".

日本語の概要は準備中です。原文の説明を表示しています。

Audits websites for AI search visibility (GEO/SEO) and generates deployable artifacts (llms.txt, schema JSON-LD, robots.txt). 7-dimension scorecard tailored by site type and size, grounded in Princeton KDD 2024, Toronto 2025, and ICLR 2026 research. This skill should be used when optimizing for ChatGPT, Perplexity, Google AI Overviews, or other AI search engines. Also triggered by queries about AI search optimization, generative engine optimization, llms.txt, AI crawler configuration, schema markup for AI, citation optimization, or Google AI Mode.

日本語の概要は準備中です。原文の説明を表示しています。

Validate SEO and LLM-readability claims against live HTML, local fixtures, and generated artifacts. Use this skill when the user asks to prove whether title, meta description, canonical, hreflang, JSON-LD, NewsArticle.image, OpenGraph, Twitter cards, RSS autodiscovery, robots.txt, llms.txt, sitemap, news-sitemap, crawler access, or performance evidence is actually present, and when subjective audits must become timestamped pass/fail reports.

日本語の概要は準備中です。原文の説明を表示しています。

Design deterministic technical SEO and schema.org guidance for crawlable public pages. Use this skill when the user asks for title and meta description rules, canonical and hreflang tags, JSON-LD schema, NewsArticle, Article, TechArticle, BreadcrumbList, WebSite, Organization, Person, OpenGraph, Twitter cards, sitemap, news-sitemap, RSS, robots.txt, llms.txt, publisher logo, ImageObject, or metadata templates that must match visible content.

日本語の概要は準備中です。原文の説明を表示しています。

Escalate blocked scraping campaigns with provider-neutral proxy rotation — decide between datacenter, residential, and mobile pools, integrate rotation with scrapling, configure session stickiness for stateful flows, monitor cost and health, and stay inside legal and ethical boundaries. Use as the next step after `headless-web-scraping` client-side stealth (StealthyFetcher, rate limiting, robots.txt) is insufficient and traffic is legitimate.

日本語の概要は準備中です。原文の説明を表示しています。

Rate limiting for serverless and edge apps with the @upstash/ratelimit TypeScript/JavaScript SDK backed by Upstash Redis. Use when adding a rate limiter or throttling to an API route, Next.js middleware, Vercel Edge, Cloudflare Workers, or any HTTP endpoint; returning 429 Too Many Requests; choosing between fixed window, sliding window, and token bucket algorithms; limiting per user, IP, API key, or tenant with prefixes and custom keys; protecting login, signup, form, or AI endpoints from abuse, bots, and brute force; using deny lists, ephemeral caching, analytics, timeouts, and multi-region rate limits; or estimating the Redis command cost of rate limiting. Also use when the user says rate limit, rate-limiting, throttle, quota, request limits, or traffic protection.

日本語の概要は準備中です。原文の説明を表示しています。

Generative Engine Optimization plus agent readiness. Use this skill whenever the user asks about GEO, AEO, LLMO, optimizing content for AI search engines (ChatGPT, Perplexity, Google AI Overviews, Claude, Gemini, Copilot), getting cited by LLMs, brand mentions in AI responses, llms.txt, robots.txt for AI crawlers, Schema.org JSON-LD, FAST framework, agent readiness, MCP server discovery, Web Bot Auth, OAuth for agents, API Catalog, agentic commerce (x402, ACP, UCP), Markdown content negotiation, or auditing a site or page for AI visibility. Also trigger when the user says "AI SEO", asks how to "rank in ChatGPT", "show up in Perplexity", "appear in AI Overviews", or wants a site to "speak to AI agents". Trigger even when the request is implicit, such as "review this article so AI search picks it up" or "make our docs agent-friendly".

日本語の概要は準備中です。原文の説明を表示しています。

"Design conversational AI chatbots including intent recognition, slot filling, dialogue flow, and response generation. Use this skill when the user needs to build a chatbot, design conversation flows, implement intent classification, or improve chatbot accuracy — even if they say 'build a chatbot', 'our bot doesn't understand users', 'design a FAQ bot', or 'improve our chatbot's responses'.".

日本語の概要は準備中です。原文の説明を表示しています。

Test Retrieval-Augmented Generation (RAG) systems for data poisoning, prompt injection via retrieved documents, and data exfiltration through manipulated context windows. Use this skill when assessing RAG-based chatbots, knowledge bases, enterprise AI assistants, or any system that augments LLM responses with external document retrieval. Covers document injection, embedding manipulation, knowledge base poisoning, and cross-document inference attacks.

日本語の概要は準備中です。原文の説明を表示しています。

Test Large Language Models for direct prompt injection vulnerabilities where user input overrides system instructions, extracts system prompts, bypasses safety filters, or causes unauthorized actions. Use this skill when assessing chatbots, AI assistants, LLM-powered tools, or any application that processes natural language input through an LLM. Covers role-playing attacks, instruction hierarchy exploitation, multi-turn manipulation, and context window abuse for comprehensive AI security testing.

日本語の概要は準備中です。原文の説明を表示しています。

Identify and exploit default or weak credentials on web application login forms, admin panels, CMS backends (WordPress wp-admin, Joomla, Drupal), and embedded device management interfaces. Signals include framework fingerprinting (WhatWeb, Wappalyzer, Nikto), exposed admin paths from robots.txt/dirbusting, and weak password policy acceptance of "Password1" or "123456". Tools: Burp Suite Intruder, Hydra, Medusa, OWASP ZAP.

日本語の概要は準備中です。原文の説明を表示しています。

Sweep a PR's automated + human review comments and act on them — especially for material (large / logic-bearing) PRs. Handles "sweep the PR comments", "check PR review feedback", "address review comments", "did the bots flag anything", and the pre-/post-merge review pass on any non-trivial PR.

日本語の概要は準備中です。原文の説明を表示しています。

Full-funnel paid advertising operations for B2B SaaS. Use this skill for PPC strategy, Google Ads optimization, LinkedIn Ads, social media advertising, programmatic buying, creative strategy, attribution modeling, budget allocation, budget pacing and planned-vs-delivered reconciliation, audience overlap and campaign self-competition audits, suppression lists, ROAS improvement, media spend optimization, and the media no auction sells — newsletter and podcast sponsorships, community and industry-publication placements, paid review-site listings on G2 and Capterra, and pay-per-lead content syndication. It also covers buying on the AI answer surface — ads inside Google AI Overviews and AI Mode that existing Search, Shopping and Performance Max campaigns already serve into with no opt-out, no placement targeting and no segmented reporting, and ChatGPT Ads and Microsoft Copilot as separate opt-in platforms with their own plan-tier reach limits, no negative keywords, and a landing-page crawler gate. It also owns the conversion signal the bidding algorithms learn from — CRM pipeline stages (SQL, opportunity, closed-won) sent back to Google Ads, LinkedIn, Meta and Microsoft Ads through offline conversion import, enhanced conversions for leads, the Google Data Manager API and the LinkedIn Conversions API, with click-ID capture, stage values, dedupe, EEA consent signals and retractions. It also gates connected TV (CTV) and streaming video for B2B — whether a reach medium belongs in the plan, how a vendor ties a TV household to a target account (member data, IP-to-account graph or contextual), the server-side ad insertion (SSAI) fraud questions, Programmatic Guaranteed deals, and a holdout lift test because CTV has no click. It also runs person-led paid social — LinkedIn Thought Leader Ads and Meta partnership ads that put spend behind an employee's or creator's post — on a paid-usage term, an in-post disclosure check and an end-date register, because the platform approval carries no term. Also triggers on: CTV, connected TV, OTT, streaming TV ads, should we run CTV, LinkedIn CTV, B2B CTV, account-based CTV, SSAI fraud, thought leader ads, boost an employee's post, sponsor a creator's post, partnership ads, whitelisting, creator usage rights, PPC, Google Ads, LinkedIn Ads, social ads, programmatic, ad creative, attribution, media budget, paid campaigns, ROAS, CPA, ad spend, newsletter sponsorship, podcast sponsorship, community sponsorship, sponsor a newsletter, content syndication, pay-per-lead, cost per lead vendor, media kit, rate card, insertion order, direct buy, publisher partnership, make-good, G2 paid listing, Capterra ads, review site advertising, sponsorship ROI, budget pacing, we underspent our budget, are our campaigns competing with each other, audience overlap, self-competition, campaign cannibalization, suppression list, exclusion list, ad frequency across channels, how many ad accounts do we have, ads in AI Overviews, AI Mode ads, ChatGPT Ads, OpenAI Ads Manager, Copilot ads, conversational ads, should we advertise on ChatGPT, can we buy our way into the AI answer, our ads are showing in AI Overviews and we cannot report on it, context hints, OAI-AdsBot, our ad landing page fails review, robots.txt is blocking our ads, our paid leads are junk, Google Ads is optimizing for the wrong leads, offline conversion import, OCI, enhanced conversions for leads, send CRM stages back to Google Ads, upload SQLs to LinkedIn, LinkedIn Conversions API, LinkedIn CAPI, Meta conversion leads, CRM to ad platform, gclid, li_fat_id, msclkid, value-based bidding, optimize for pipeline not form fills, low match rate, conversion lag.

日本語の概要は準備中です。原文の説明を表示しています。

Technical SEO audit across 8 categories: crawlability, indexability, security, URL structure, mobile, Core Web Vitals, structured data, and JavaScript rendering. Enhanced with live GSC (indexing status, crawl data) and Ahrefs (backlink profile) data when MCPs are available. Use when user says "technical SEO", "crawl issues", "robots.txt", "Core Web Vitals", "site speed", or "security headers".

日本語の概要は準備中です。原文の説明を表示しています。

Comprehensive SEO analysis for any website or business type. Orchestrates 52 sub-skills (52 active): full site audits, technical SEO (CWV/INP), schema, E-E-A-T content quality, images, sitemaps, GEO for AI Overviews, llms.txt generation, AI crawler audit, plus live GSC and Ahrefs MCP data. GSC: overview, drops, opportunities, brand-vs-nonbrand, cannibalization, compare, content-decay, index-issues, new-keywords. Ahrefs: overview, backlinks, keywords, competitors, content-gap, broken-links, new-links, anchor-analysis, dr-history, top-pages. Cross-MCP: serp, content-brief, brand-radar, site-audit-pro, report. Local: log-analysis, ai-content-check, internal-links, local, migration-check, obsidian-kb. AI Readability: llms-txt, robots-ai. Performance: lighthouse-audit, core-web-vitals, page-experience. Quality & AI Search: rich-results, ai-optimization, eeat-audit, helpful-content. Triggers on: "SEO", "audit", "schema", "Core Web Vitals", "sitemap", "E-E-A-T", "AI Overviews", "GEO", "technical SEO", "content quality", "structured data", "GSC", "Ahrefs", "backlinks", "keywords", "search console", "domain rating", "local SEO", "migration", "lighthouse", "pagespeed", "LCP", "INP", "CLS", "page experience", "interstitials", "mobile friendly", "rich results", "rich snippets", "schema eligibility", "AI optimization", "AI search readiness", "EEAT", "trust signals", "helpful content", "people-first", "content quality gate".

日本語の概要は準備中です。原文の説明を表示しています。