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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.

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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.

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Analyze server log files for crawl budget insights. Reads Apache Combined/Common or Nginx access logs locally (no external calls). Classifies bot vs user traffic, identifies top crawled URLs, crawl frequency by path, and crawl budget concerns. Use when user says "log analysis", "crawl budget", "server logs", "bot traffic", "crawl frequency", "access log", "analyze logs".

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Review Dependabot PRs efficiently: triage, risk assessment, batching, and auto-merge policies. Use when dependency update PRs pile up or you want a sane update workflow.

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Design chatbot user interfaces — message layouts, suggestion chips, rich cards, feedback controls, and accessibility. Use when designing the visual and interaction layer of conversational UIs.

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Authoring and managing Agentforce agent definitions using the declarative Agent Script DSL (.agent files) and associated metadata types, including the Agent Script language for the new Agentforce Builder (hybrid-reasoning -> logic vs | prompt instructions, @actions/@subagent/@variables references, subagents). Use when creating agents in source control, writing or debugging Agent Script, debugging agent metadata, or understanding the metadata lifecycle of GenAiPlugin/GenAiPlanner/BotVersion types. Triggers: 'how do I deploy an Agentforce agent using source control', 'convert an agent topic to a subagent', 'what metadata types make up an Agentforce agent', 'agent test run command failing in CI pipeline', 'GenAiPlugin vs GenAiPlanner metadata relationship', 'Agent Script logic vs prompt instructions'. NOT for Apex-based agent actions — use agentforce/custom-agent-actions-apex. NOT for clicking the agent together in the Builder UI — use agentforce/agentforce-agent-creation.

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Use when designing how an Agentforce agent transfers the conversation to a human agent (Omni-Channel), to another bot/agent, or to an alternate workflow — including context package, deflection, escalation triggers, and user messaging. Triggers: 'agent to human handoff', 'agentforce escalate to omni channel', 'agent to agent handoff', 'transfer conversation with context', 'agent deflection fallback'. NOT for topic scope and selector design — use agentforce/agent-topic-design. NOT for the overall Einstein Bot plus Agentforce estate topology — use architect/conversational-ai-architecture.

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Add Agent Swarm (Teams) support to Telegram. Each subagent gets its own bot identity in the group. Requires Telegram channel to be set up first (use /add-telegram). Triggers on "agent swarm", "agent teams telegram", "telegram swarm", "bot pool".

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Advanced OpenClaw skill creation handler that executes the official 5-step research flow with comprehensive analysis and best practices. Ensures proper methodology when users request to create or modify OpenClaw/Moltbot/ClawDBot skills following official standards.

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A moderated imageboard for AI agents to post and debate. A place made by bots for bots to post what they are really thinking

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Stop AI agents from secretly bypassing your rules. Mechanical enforcement with git hooks, secret detection, deployment verification, and import registries. Born from real production incidents: server crashes, token leaks, code rewrites. Works with Claude Code, Clawdbot, Cursor. Install once, enforce forever.

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Designs and analyzes in vivo CRISPR screens in animal tumor models, organoids, and immune-cell adoptive transfers. Covers bottleneck math (250x cells/sgRNA requires ~25M cells implanted; impossible for most syngeneic models, forcing focused libraries), focused library design (Manguso 2017 Nature 547:413 immune screen; Chen 2015 tumor screens), CRISPR-StAR intrinsic-control screening (Uijttewaal 2025 Nat Biotechnol 43:1848), clonal-dynamics-limited detection, tumor-explant DNA recovery, syngeneic vs xenograft vs PDX considerations, and the relationship to downstream MAGeCK / drugZ analysis. Use when designing in vivo CRISPR screens for tumor / immune / metastasis biology, choosing focused vs genome-wide for animal models, addressing bottleneck-induced clonal collapse, picking the syngeneic / xenograft / PDX model, integrating in vivo with in vitro results, or applying CRISPR-StAR for animal experiments.

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This skill guides evaluation of venous thromboembolism (VTE) risk factors in Cushing's syndrome patients to prevent thrombotic complications. Use when assessing a CS patient for thrombotic risk, especially perioperatively; triggers include preoperative assessment, postoperative period (within 4-6 weeks), or presence of CS with additional risk factors such as prior VTE, immobilization, malignancy, or estrogen use.

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Standard operating procedure for producing a documentation page end to end — gather source material, classify, draft against the measured corpus profile, then run the reader-level and humanizer passes and both gates. Use for any page on a documentation surface, or when rewriting a page that reads as machine-written. Orchestrates technical-writing, reader-level and humanizer in a fixed order.

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Use when the user asks to design a multi-agent system, pick an orchestration pattern (supervisor/swarm/pipeline), generate tool schemas for agents, or evaluate agent execution logs for cost, latency, and failure bottlenecks. Examples: 'design an agent architecture for research automation', 'generate Anthropic tool schemas from these tool descriptions', 'analyze these agent run logs for bottlenecks'. NOT for Claude Code workflow files (use workflow-builder) or single-agent prompt design (use agent-workflow-designer).

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Build monitoring bots that poll APIs and send notifications on state changes (new listings, price alerts, status updates)

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Build the Clawdbot macOS menu bar app.

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Use when constructing the finance-side forecast — top-down vs bottom-up shape, confidence bands, retro-loop. Triggers on 'build the forecast model', 'reconcile top-down with bottom-up'.

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Framework para construir aplicações com LLM usando agentes, chains e RAG. Suporta múltiplos provedores (OpenAI, Anthropic, Google), 500+ integrações, agentes ReAct, tool calling, gerenciamento de memória e recuperação de vector stores. Use para construir chatbots, sistemas de perguntas e respostas, agentes autônomos ou aplicações RAG. Ideal para prototipagem rápida e deployments em produção.

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Author a complete both-seats coaching lesson for a BBA-NATIVE bidding scenario and produce all served artifacts in one consistent pass: curate the pool → tokenized coaching-curated/<scn>.pbn → gated promote to served coaching/<scn>.pbn → resolve to South=student coaching-non-rotated/<scn>.pbn (bridge-classroom) → update both toc.json files. Invoke as `/coach-lesson <Scenario>` (e.g. `/coach-lesson Fourth_Suit_Forcing`). Use ONLY for conventions BBA bids natively (its bba/<scn>.pbn [Auction] is the answer key — Basics, New_Minor_Forcing, Fourth_Suit_Forcing). For conventions BBA CANNOT bid (Spiral Raises), use the py/spiral_auction.py substitution path instead — not this skill.

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Cloudflare Turnstileをprojectへend-to-endで導入する。codebaseを調査し、Cloudflare APIでwidgetを作成し、適切なformへ埋め込み、既存backendへ正式なserver-side siteverifyを接続して検証する。Turnstile追加、CAPTCHA設定、botからのform保護、Turnstile連携修正を依頼されたときに使用する。developers.cloudflare.com/turnstile/spinの中核手順へAIDD固有の安全規則を重ねたSkill。

Add Agent Swarm (Teams) support to Telegram. Each subagent gets its own bot identity in the group. Requires Telegram channel to be set up first (use /add-telegram). Triggers on "agent swarm", "agent teams telegram", "telegram swarm", "bot pool".

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。

Add Agent Swarm (Teams) support to Telegram. Each subagent gets its own bot identity in the group. Requires Telegram channel to be set up first (use /add-telegram). Triggers on "agent swarm", "agent teams telegram", "telegram swarm", "bot pool".

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Detect AWS IAM privilege escalation paths using boto3 and Cloudsplaining policy analysis to identify overly permissive policies, dangerous permission combinations, and least-privilege violations

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