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概要と使いどころ
sgcop の RuboCop 設定を、導入先プロジェクトの .rubocop.yml にセットアップ・更新する。標準（rubocop.yml）か厳格版（rubocop_strict.yml）かの導入方針をまず確認して inherit_gem を整え、既存 .rubocop.yml から sgcop と重複する不要設定を削除する。gem 依存のカスタム Cop（enumerize 系など）は必要時のみ確認。そのうえで rubocop --auto-gen-config で .rubocop_todo.yml を生成し、違反（ノイズ）が多い Cop は無効化・Exclude・段階対応を提案、無効化したら todo を作り直す。
Cloud security attack methodology covering AWS, Azure, and GCP. Includes credential harvesting (IMDS, ~/.aws, env vars, leaked CI secrets, instance roles), enumeration with cloud-specific tools (pacu, ScoutSuite, Prowler, ROADtools, gcp_enum), privilege escalation paths (IAM PassRole, AssumeRole chains, Lambda/Functions privilege flips, Azure Owner-on-self, GCP serviceAccountTokenCreator), persistence techniques (IAM user/key creation, AAD app registration, GCP svc account key creation, EventBridge/Logic Apps backdoors), data exfiltration (S3/Blob/GCS, snapshot share, RDS/CosmosDB/Cloud SQL exfil), cloud-native lateral movement (cross-account assume, Azure AD multi-tenant, GCP project hierarchy), serverless attacks (Lambda env vars, layer hijack, Step Functions), Kubernetes-on-cloud (EKS/AKS/GKE-specific paths to node and AWS metadata), and CSPM evasion (CloudTrail blind spots, GuardDuty mute, Sentinel rule shaping). Use when the engagement scope is cloud accounts, when you've stolen cloud credentials, or...
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Provides safety-critical validation, guardrails, and data reduction for gcloud CLI operations across Google Cloud Platform (GCP) services and infrastructure. Use when planning, generating, constructing, proposing, describing, or executing any gcloud CLI commands - including when answering questions about gcloud syntax, or formatting flags. Don't use when writing Google Cloud client library code or raw REST/gRPC API requests.
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Cloud IAM red-team attack chain across AWS, Azure, GCP — focused on EXTERNAL exploitation paths and post-credential-discovery privilege analysis. Covers IAM enumeration (aws iam, az role, gcloud iam), STS/AssumeRole chaining, Azure Managed Identity abuse (via SSRF/leak), GCP service account JSON abuse, IMDSv1/v2 attacks via SSRF, K8s ServiceAccount token privilege analysis once held (token discovery / cluster exposure is owned by hunt-k8s), role-trust-policy confused-deputy, cross-account assume-role enumeration, IAM privilege escalation patterns (24+ AWS, 8+ Azure, 6+ GCP), and AWS Cognito Identity Pool unauthenticated-role attack chain (GetId → GetCredentialsForIdentity → IAM role abuse). Built for the case where recon yields a credential (key, JSON, token) and you need to know what it grants and how to escalate. Use when an AWS key / Azure secret / GCP service account JSON / K8s SA token surfaces from a code repo, JS bundle, APK, breach corpus, or SSRF chain.
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Scaffold a minimal local LangChain agent in TypeScript by following the official quickstart. Use when the user wants to quickly build or try a LangChain agent locally.
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Scaffold a minimal local LangChain agent in Python by following the official quickstart. Use when the user wants to quickly build or try a LangChain agent locally.
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Use when someone outside the marketing team has to film — a customer for UGC, an employee for EGC, or a paid creator or KOC — and needs a brief: talking points, shooting guide, do and do-not list, usage rights, deliverables, and batch management. Trigger on 'UGC brief', 'creator brief', 'KOC brief', 'brief for employee videos', 'what do I tell the influencer', 'we hired a creator to film'. Also use when the user asks how to get customers to make videos for the brand. Not for — a script the team writes and shoots itself, see `04-script-video-global`; edit direction for footage already shot, see `44-video-editor-brief-global`; posting inside communities, see `38-community-seeding-global`.
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Trigger for: FFP IGCE, firm-fixed-price estimate, FFP cost model, proposed FFP rate validation, wrap-rate analysis, Agency BPA rate comparison, price-reasonableness memo, or fair-and-reasonable analysis. Build auditable Firm-Fixed-Price federal estimates using BLS OEWS wages, layered fringe/overhead/G&A/profit, GSA CALC+ positioning, and GSA Per Diem travel. Use for FFP-by-period, FFP-by-deliverable, SOW/PWS decomposition, implied-multiplier analysis, and fixed-price scenario comparisons. Do NOT use for Labor Hour, T&M, or cost-reimbursement IGCEs (use IGCE Builder LH/T&M or IGCE Builder CR). Do NOT use for grant budgets. Requires the bls-oews, gsa-calc, and gsa-perdiem MCP servers.
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改写中文学术论文中被知网AIGC检测器标为"红色显著"的段落，目标是将AI率落出红色区间且不改变事实/数字/术语/引用。基于实战将20.6%降至10.1%（净降10.5个百分点）的工作流提炼。使用场景：用户提到"知网AIGC""降AI率""红色显著""降重"或贴出AIGC检测报告片段时触发。
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Provides safety-critical validation, guardrails, and data reduction for gcloud CLI operations across Google Cloud Platform (GCP) services and infrastructure. Use when planning, generating, constructing, proposing, describing, or executing any gcloud CLI commands - including when answering questions about gcloud syntax, or formatting flags. Don't use when writing Google Cloud client library code or raw REST/gRPC API requests.
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Produce a UGC-style talking-head video ad end to end on the MaxFusion MCP — research the product with user-supplied competitor leads, tear down 5 competitor Meta ads and 5 organic TikToks, write a pain-driven script that sounds like a person talking (never like an ad), reverse-prompt a rights-clean photoreal actor from a user-supplied reference photo, generate two chained 10-second Gemini Omni clips that play as one continuous take, and ship a single seamless 9:16 MP4. Use whenever the user wants a UGC ad, a talking-head ad, an ad for an app or product, mentions Omni or Gemini Omni Flash, drops an actor photo and asks for a video ad, or says anything like "make me some UGC", "let's make ads for X", or "another variation". Built for Claude Code (local ffmpeg); degrades to Claude app with documented fallbacks.
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gogcli（gog コマンド）の専門家スキル。Google Workspace と関連サービス25以上（Gmail, Calendar, Chat, Drive, Sheets, Docs, Slides, Tasks, Keep, Contacts, People, Groups, Admin, Classroom, Forms, Meet, Maps, YouTube, Photos, Sites, Analytics, Search Console, Apps Script, Zoom）をターミナルから操作するGoベースCLIツールの使い方を支援。OAuth2/サービスアカウント認証、マルチアカウント管理、自動化・エージェント安全機能を提供。Use when working with Google Workspace services via CLI, managing Gmail/Calendar/Drive/Sheets, automating Google Workspace tasks, or setting up gogcli authentication.
エージェント、メモリ、ツール統合パターンを備えたLangChainフレームワークを使用してLLMアプリケーションを設計します。LangChainアプリケーションの構築、AIエージェントの実装、または複雑なLLMワークフローの作成時に使用します。
Cloud IAM red-team attack chain across AWS, Azure, GCP — focused on EXTERNAL exploitation paths and post-credential-discovery privilege analysis. Covers IAM enumeration (aws iam, az role, gcloud iam), STS/AssumeRole chaining, Azure Managed Identity abuse (via SSRF/leak), GCP service account JSON abuse, IMDSv1/v2 attacks via SSRF, K8s ServiceAccount token privilege analysis once held (token discovery / cluster exposure is owned by hunt-k8s), role-trust-policy confused-deputy, cross-account assume-role enumeration, IAM privilege escalation patterns (24+ AWS, 8+ Azure, 6+ GCP), and AWS Cognito Identity Pool unauthenticated-role attack chain (GetId → GetCredentialsForIdentity → IAM role abuse). Built for the case where recon yields a credential (key, JSON, token) and you need to know what it grants and how to escalate. Use when an AWS key / Azure secret / GCP service account JSON / K8s SA token surfaces from a code repo, JS bundle, APK, breach corpus, or SSRF chain.
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使用 qingcloud CLI 操作青云 QingCloud。当用户提到青云、QingCloud、青云云、青云QingCloud 等时触发此技能。
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エージェントの過去の会話や資料をPineconeに保存し、関連情報を検索して回答に使う仕組みを構築。セッションをまたぐ長期記憶や、意味に基づく検索の試作を支援します。
Design GCP architectures for startups and enterprises. Use when asked to design Google Cloud infrastructure, deploy to GKE or Cloud Run, configure BigQuery pipelines, optimize GCP costs, or migrate to GCP. Covers Cloud Run, GKE, Cloud Functions, Cloud SQL, BigQuery, and cost optimization.
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Stores, retrieves, and manages data as objects in Cloud Storage on Google Cloud (also known colloquially as GCS) buckets. Use when you need to interact with Cloud Storage — set up a Storage MCP server (remote or local Toolbox), create or configure buckets, upload, download, stream, or transfer data, organize objects with folders, generate signed URLs, control access (IAM, ACLs, public access prevention), set storage classes (Standard, Nearline, Coldline, Archive), manage lifecycle and cost, protect data (versioning, CMEK, retention, Bucket Lock, holds, soft delete), host static websites, trigger Pub/Sub notifications, mount buckets (gcsfuse), or optimize performance. Covers gcloud storage / gsutil, JSON/XML APIs, client libraries, Terraform, and Cloud Storage MCP servers. Don't use for non-Storage MCP servers, block storage (Persistent Disk), BigQuery, or databases (Cloud SQL, Spanner, Bigtable, Firestore).
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Post-access cloud exploitation for AWS, GCP, and Azure — what to do AFTER you obtain credentials or reach a metadata endpoint. Covers IAM enumeration and privilege escalation (iam:PassRole, CreatePolicyVersion, AssumeRole chains, GCP service-account impersonation, Azure managed-identity abuse), IMDSv1/v2 metadata credential theft, STS token abuse, S3/GCS/Blob bucket takeover and object exfil, Lambda/Cloud Functions env-var secrets, cross-account and cross-service pivoting, and turning leaked keys into demonstrated impact (read PII, assume admin, exfil data). Assumes authorized scope only. Use when you have AWS/GCP/Azure keys, an SSRF hitting 169.254.169.254 / metadata.google.internal, a leaked service-account JSON, or a token, and need to escalate and prove impact. For finding buckets/origins first, use cloud-recon; for the SSRF entry point, see web2-vuln-classes. 中文触发词：云渗透、AWS提权、IAM枚举、元数据凭证、云安全审计
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Bugcrowd-specific reporting tactics complementing report-writing: VRT category search-and-fallback strategy when no exact match exists, manual severity override when VRT defaults underrate impact, severity-request paragraph as first body section, OOS-clause rebuttal templates (rate limiting on auth-flow endpoints, debug-info framing, user-enumeration with sensitive PII, theoretical-issue counter), chained-finding cross-reference patterns, target selection for QA-vs-prod programs, researcher-side hygiene (Bugcrowdninja email alias, account state restoration, friendly-tester posture). Use when filing a Bugcrowd submission, when VRT default seems wrong, when triager closes as OOS or downgrades severity, when chaining linked submissions, or when scope distinguishes production from QA. Pairs with report-writing and triage-validation.
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发现用户生成内容（UGC）。搜索与创作者品牌/账号相关的粉丝内容、测评、提及和社区讨论， 输出高价值 UGC 列表与互动建议。当用户说"谁提到了我"、"粉丝内容"、"品牌提及"、 "UGC 发现"、"用户口碑"、"测评搜索"、"社区讨论"时触发。
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Linting best practices and golangci-lint configuration for Golang projects — running linters, configuring .golangci.yml, suppressing warnings with nolint directives, interpreting lint output, and selecting linters. Use when configuring golangci-lint, asking about lint warnings or nolint suppressions, setting up code quality tooling, or choosing linters. Also use when the user mentions golangci-lint, go vet, staticcheck, or revive. Not for wiring a lint step into a GitHub Actions pipeline (→ See `samber/cc-skills-golang@golang-continuous-integration` skill).
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When the user wants to plan, brief, source, or measure organic creator / influencer / UGC marketing for their app — including TikTok creators, Instagram Reels, YouTube Shorts, micro-influencers, paid creator briefs, UGC ad creative for Meta/TikTok, affiliate programs, and seeding strategy. Use when the user mentions "creators", "influencers", "TikTok marketing", "UGC", "user-generated content", "creator briefs", "creator outreach", "influencer marketing", "Reels", "Shorts", "creator gifting", "seeding", "affiliate", "Whop", "TikTok Spark Ads", "Instagram collab posts", or "I want my app to go viral on TikTok". For paid social ad campaigns (Meta/TikTok ad accounts), see ua-campaign. For PR / press, see press-and-pr. For viral in-app loops, see referral-program.
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INVOKE THIS SKILL when setting up a new project or when asked about package versions, installation, or dependency management for LangChain, LangGraph, LangSmith, or Deep Agents. Covers required packages, minimum versions, environment requirements, versioning best practices, and common community tool packages for both Python and TypeScript.
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