'ops' 검색 결과

Use when you need Azure DevOps CLI guidance to verify installation, configure organization and project context, discover work item IDs by optional WIQL filters, and execute safe work-item create/update operations. Uses an interactive install gate - if `az` or the Azure DevOps extension is missing, ask whether to show installation guidance before any work item commands. This should trigger for requests such as Azure DevOps work item list; List Azure Boards work item IDs; Azure DevOps WIQL query; Azure DevOps CLI planning workflow. Part of Plinth Toolkit

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Expert in designing and optimizing growth loops - self-reinforcing systems where the output of one cycle becomes the input for the next. Covers viral loops, content loops, paid loops, sales loops, and product loops. Knows how to identify, measure, and accelerate the specific loop mechanics that drive sustainable growth. Use when "growth loop, viral loop, content loop, flywheel, compounding growth, acquisition loop, referral loop, " mentioned.

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/aegisops-ai — Autonomous Governance Orchestrator workflow skill. Use this skill when the user needs Autonomous DevSecOps & FinOps Guardrails. Orchestrates Gemini 3 Flash to audit Linux Kernel patches, Terraform cost drifts, and K8s compliance and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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Set up SOPS + age encryption for sharing .env files securely across machines. Detects existing state, installs tools, generates age keys, creates .sops.yaml, and encrypts .env files as YAML (avoids SOPS dotenv bug #1435). Use when user mentions "sops setup", "encrypt env", "share secrets", "secure env files", "sops age setup", "env encryption", "setup sops", "share env across machines".

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Storybook에서 프로젝트의 기존 UI 구성 요소와 설정 항목, 사용 예시를 확인합니다. 사용법 질문에 답하고 중복 구현 전에 재사용 가능 여부를 판단합니다.

• 기존 UI 구성 요소를 찾습니다
• 구성 요소의 설정 항목과 사용 예시를 확인합니다
• 구성 요소 사용법을 질문합니다

Search software, data, and engineering jobs across countries through freehire.me. Filter by skills, seniority, location, posting age, and remote work, and retrieve full descriptions to assess opportunities or inspect a specific posting.

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• Find remote React jobs in the EU
• Search recent DevOps openings in Germany
• Compare senior backend engineering roles

Set up ArgoCD to keep Kubernetes deployments aligned with configuration stored in Git, an approach called GitOps. Follow guidance for multiple environments, automatic synchronization, deployment ordering, access permissions, and troubleshooting differences.

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• Set up Kubernetes deployments driven by Git changes
• Manage staging and production configurations
• Configure synchronization order and pre-deployment jobs

Guide reviews of Linux Kernel patches for memory safety, Terraform plans for costly resource changes, and Kubernetes configurations for restricted permissions. A separately installed tool and configured AI model produce advisory findings and candidate manifests for validation.

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• Review Linux Kernel patches for memory safety issues
• Check Terraform plans for potentially costly resource changes
• Draft Kubernetes permission settings from security requirements

Create and review company procedures and operational guides, then audit internal wikis for outdated pages, missing owners, broken connections, and inconsistent terminology. Produce structured drafts, step checks, and a prioritized list of documents to improve.

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• Drafting procedures for employee onboarding
• Checking operational guides before use
• Prioritizing outdated wiki pages for revision

Operate KubeSphere DevOps pipelines within a permitted project using KubeSphere APIs and OAuth authentication. Create pipelines, run selected branches, monitor execution, and retrieve logs or build artifacts without requiring cluster administrator access or direct Jenkins access.

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• Creating pipelines within an authorized project
• Building a selected repository branch
• Checking run status, logs, and build artifacts

Create Kubernetes deployment files and Helm charts, reusable application packages. Configure permissions, network isolation, and persistent storage, then investigate pod failures and resource usage to adjust workloads and verify deployment health.

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• Create deployment YAML and Helm charts
• Configure access permissions and network isolation
• Set up persistent storage and sensitive configuration

Refactor React components that have too many true-or-false settings into reusable, flexible parts. This skill guides component composition, shared state, and API design, with examples and separate guidance for React 19 features.

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• Refactoring components with many boolean props
• Designing a reusable component library
• Organizing state shared by sibling components

Use Chainbase CLI to investigate blockchain records, including token holders, prices, wallet activity, and DeFi positions. Use Tops to discover trending crypto topics, inspect related posts, and track recent Twitter/X mentions of projects or keywords.

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• Check major token holders and transfer history
• Review wallet balances and DeFi positions
• Run custom SQL queries on blockchain records

Plan and configure Kubernetes deployments, Git-based continuous delivery, and cloud resources defined in code. Covers Helm, Kustomize, ArgoCD, Flux, Terraform, Pulumi, and AWS CDK, with patterns for environment separation, secrets, validation, updates, and rollback.

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• Create Helm charts and environment-specific configurations
• Set up Git-based delivery with ArgoCD or Flux
• Organize cloud resources with Terraform or Pulumi

Organize shared build settings, tasks, and package versions across .NET projects. Review Directory.Build file placement and import order, centralize repeated configuration, and retain the settings that belong to individual projects or folders.

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• Centralizing repeated build settings across projects
• Managing shared NuGet package versions
• Fixing imports in nested Directory.Build files

Apply the same operation to a folder of images, videos, or audio files, including compression, watermarks, format conversion, resizing, and volume normalization. Save processed copies separately and receive a summary of successes and failures.

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• Compress a folder of images
• Add the same watermark to multiple images
• Convert multiple videos to a vertical 9:16 layout

Set up Azure Pipelines for CI/CD, configure build and release pipelines, manage Azure DevOps projects, and integrate with Azure services. Use when working with Azure DevOps Services or Server for enterprise DevOps workflows.

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Define lifecycle stages and marketing → sales / CSM handoff rules for leads captured by GTM channels during PRD v0.8 Deployment & Ops. Triggers on requests to set up lead lifecycle, define MQL/SQL criteria, build handoff process, or when user asks "what's an MQL?", "marketing to sales handoff", "lead lifecycle", "lead routing", "RevOps", "MOPS", "marketing operations". Outputs BR-MOPS-* lifecycle rules and GTM-MOPS-* handoff flow entries.

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公众号写作助手 (微信公众号文章 全链路 — 选题 / 标题 / 开篇 / 结构 / 行文 / 排版 / 配图 / 推送 / 涨粉 / 留言 / 二次传播 / 变现, 单 artifact = 一篇公众号推文) (WeChat Official Account article writing — 微信公众号「文章」这个 artifact 的写作、生产、分发、变现 (单篇文章为单位的 craft + ops + 商业化, 不含 SCRM / 私聊 / 群运营 / 朋友圈 SOP — 那些归 private-domain-ops)) Master OS — automated mastery of WeChat Official Account article writing — 微信公众号「文章」这个 artifact 的写作、生产、分发、变现 (单篇文章为单位的 craft + ops + 商业化, 不含 SCRM / 私聊 / 群运营 / 朋友圈 SOP — 那些归 private-domain-ops): top builders' mental models, tool stack, current workflows, jargon, and where to keep up. Trigger this skill when the user works on WeChat Official Account article writing — 微信公众号「文章」这个 artifact 的写作、生产、分发、变现 (单篇文章为单位的 craft + ops + 商业化, 不含 SCRM / 私聊 / 群运营 / 朋友圈 SOP — 那些归 private-domain-ops) problems and wants industry-grade thinking, tool selection, or workflow guidance. 触发词：「公众号」「公众号写作」「公众号运营」「微信公众号」「服务号」

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红队渗透 / 攻防 — 受授权的红队作业者 + 渗透测试工程师 + 攻击型安全顾问的认知操作系统 (侦察 OSINT / 外网渗透 / 内网 AD 渗透 BloodHound + Kerberoasting + ADCS 利用 + 横向移动 / Web 应用渗透 OWASP WSTG / 移动 OWASP MASTG / 云渗透 AWS Azure GCP IAM 路径 + 容器逃逸 + K8s / C2 操作 Cobalt Strike Sliver Mythic Havoc + OPSEC / 初始访问 + AV EDR 绕过 (仅授权场景) / 无线 RF / 物理社工 / 报告与整改 / 框架 MITRE ATT&CK + D3FEND + PTES + OSSTMM + NIST 800-115 + Kill Chain / 法律伦理 CFAA + 网络安全法 + 刑法 285 286 + 数据安全法 + GDPR + 授权书 + 范围 + 交战规则 — 不含 黑产 / 未授权攻击 / 大规模 exploitation / 供应链投毒 / 未授权 DoS — 这是 重罪 + 行业封杀 + 律师吊销, 本 skill 严守 authorized-only 边界 — 也不含 蓝队 SOC + 恶意软件 即服务 / 僵尸网络 / 勒索软件作者 — 这是 cybercrime 不是 红队) (Cybersecurity Red Team / Offensive Security Operations — the cognitive operating system of authorized red team operators, penetration testers, and offensive security consultants covering (a) reconnaissance & OSINT (passive + active discovery, asset surface mapping), (b) external network pentest (perimeter, exposed services, web), (c) internal network / Active Directory pentest (AD enumeration via BloodHound, Kerberos abuse — Kerberoasting / AS-REP-roasting / Unconstrained delegation / S4U2self, NTLM relay, ADCS abuse, GPO abuse, lateral movement, privilege escalation), (d) web application pentest (OWASP WSTG, authentication, authorization, SSRF, XXE, deserialization, SSTI, prototype pollution, GraphQL, JWT, API), (e) mobile pentest (OWASP MASTG, iOS / Android, instrumentation Frida / Objection, MASVS), (f) cloud pentest (AWS / Azure / GCP — IAM enumeration, privilege escalation paths, container escape, K8s RBAC, serverless), (g) C2 operations & post-exploitation (Cobalt Strike / Sliver / Mythic / Havoc, beacon ops, malleable profiles, OPSEC), (h) initial access & evasion (phishing infrastructure, payload development, AV / EDR evasion, BYOVD, AMSI / ETW bypass — strictly for authorized engagements), (i) wireless / RF (WPA2/3, evil twin, Wi-Fi pivots), (j) physical / social engineering (badge cloning, pretexting, vishing — under engagement letter), (k) reporting & remediation (executive summary, technical findings, CVSS, MITRE ATT&CK mapping, retest), (l) frameworks & methodology (MITRE ATT&CK, MITRE D3FEND, PTES, OSSTMM, NIST SP 800-115, OWASP WSTG / MASTG, Cyber Kill Chain, Unified Kill Chain, Diamond Model), (m) law & ethics (CFAA US, Computer Misuse Act UK, 中国 刑法 285/286 + 网络安全法 + 数据安全法, GDPR for tested EU systems, engagement letter, scope, rules of engagement, safe harbor for bug bounty); NOT criminal hacking / 黑产 / unauthorized targeting / mass exploitation / supply-chain compromise / DoS against unconsented systems (这是 重罪 + 业内开除 + 律师执照吊销, 本 skill 严守 authorized-only 边界), NOT pure defensive blue team / SOC analyst tradecraft (是 平行学科, 仅做 边界标注 + ATT&CK 反推方向), NOT malware-as-a-service development / botnet ops / ransomware authoring (是 cybercrime 不是 红队), NOT 'ethical hacking' 在 'just curious 看看' 自我合理化的灰色操作 (违反 authorization 原则即不是 红队).) Master OS — automated mastery of Cybersecurity Red Team / Offensive Security Operations — the cognitive operating system of authorized red team operators, penetration testers, and offensive security consultants covering (a) reconnaissance & OSINT (passive + active discovery, asset surface mapping), (b) external network pentest (perimeter, exposed services, web), (c) internal network / Active Directory pentest (AD enumeration via BloodHound, Kerberos abuse — Kerberoasting / AS-REP-roasting / Unconstrained delegation / S4U2self, NTLM relay, ADCS abuse, GPO abuse, lateral movement, privilege escalation), (d) web application pentest (OWASP WSTG, authentication, authorization, SSRF, XXE, deserialization, SSTI, prototype pollution, GraphQL, JWT, API), (e) mobile pentest (OWASP MASTG, iOS / Android, instrumentation Frida / Objection, MASVS), (f) cloud pentest (AWS / Azure / GCP — IAM enumeration, privilege escalation paths, container escape, K8s RBAC, serverless), (g) C2 operations & post-exploitation (Cobalt Strike / Sliver / Mythic / Havoc, beacon ops, malleable profiles, OPSEC), (h) initial access & evasi

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数据工程 — 数据平台从业者的认知操作系统, 覆盖把数据从源系统搬运成可靠 / 可查询 / 可信赖形态供分析 / ML / 数据产品消费的全生命周期 (生成 → 摄取 → 存储 → 转换 → 服务 + 安全/数据管理/DataOps/数据架构/编排/软件工程 六条暗流, Reis & Housley 框架): 摄取与集成 (批 + CDC 变更数据捕获 Debezium + EL 工具 Fivetran/Airbyte/Meltano/dlt + Kafka Connect + schema drift) / 存储与文件表格式 (对象存储数据湖 + 列存 Parquet/ORC/Arrow/Avro + 开放表格式 Apache Iceberg/Delta Lake/Apache Hudi + lakehouse + 分区/compaction) / 转换与建模 (ELT dbt/SQLMesh + Spark + 维度建模 Kimball + Inmon + Data Vault + 大宽表 OBT + 渐变维 SCD + 增量模型 + 语义/指标层) / 编排与工作流 (Apache Airflow/Dagster/Prefect/Mage/Kestra/Apache DolphinScheduler + DAG + 幂等 + 回填 backfill + 数据资产调度) / 批流与实时 (Apache Kafka/Apache Flink/Spark Structured Streaming/Kinesis/Pulsar/Redpanda + Lambda vs Kappa + watermark/窗口/exactly-once + 流式 SQL Materialize/RisingWave + 实时 OLAP ClickHouse/Apache Druid/Apache Pinot/StarRocks/Apache Doris) / 数仓与查询引擎 (Snowflake/BigQuery/Redshift/Databricks SQL/Trino/Presto/DuckDB/Polars + 存算分离 + MPP) / 数据质量测试与可观测性 (dbt tests/Great Expectations/Soda + 数据契约 + Monte Carlo data downtime + 新鲜度/量/schema 异常检测) / 数据治理编目与血缘 (DataHub/Amundsen/OpenMetadata/Unity Catalog + 列级血缘 + PII 分类 + 访问控制 + GDPR) / DataOps 与可靠性 (数据 CI/CD + 转换版本控制 + 环境隔离 + 幂等重处理 + 数据 SLA/SLO + 计算存储 FinOps) / 数据架构范式 (现代数据栈 + lakehouse + data mesh + data fabric + 去中心化 vs 中心化所有权) / 分析工程角色 (dbt 时代连接数据工程与分析的桥) — 不含 数据科学/ML 建模本身 (是下游消费者) / BI 仪表盘制作 (serving 下游) / 数据分析报表为终点 / 'data engineer = 跑 Hadoop 的' 过时窄化 / 通用后端应用开发 (平行学科) (Data Engineering — the cognitive operating system of practitioners who design, build, and operate the data platform: moving data from source systems into reliable, queryable, trustworthy form for analytics / ML / products, covering (a) the data engineering lifecycle (generation → ingestion → storage → transformation → serving, with the undercurrents security / data management / DataOps / data architecture / orchestration / software engineering — Reis & Housley framing), (b) ingestion & integration (batch + CDC change-data-capture with Debezium, EL tools Fivetran / Airbyte / Meltano / dlt, Kafka Connect, API + file + database sources, schema drift handling), (c) storage & file/table formats (object storage data lakes, columnar formats Parquet / ORC / Arrow / Avro, open table formats Apache Iceberg / Delta Lake / Apache Hudi, lakehouse architecture, partitioning / compaction / Z-ordering), (d) transformation & modeling (ELT with dbt / SQLMesh, Spark, dimensional modeling Kimball, Inmon CIF, Data Vault, One Big Table / wide tables, normalization vs denormalization, slowly changing dimensions, incremental models, the semantic / metrics layer), (e) orchestration & workflow (Apache Airflow, Dagster, Prefect, Mage, Kestra, Apache DolphinScheduler, DAGs, idempotency, backfills, data-aware / asset-based scheduling), (f) batch vs streaming & real-time (Apache Kafka, Apache Flink, Spark Structured Streaming, Kinesis / Pulsar / Redpanda, the Lambda vs Kappa debate, watermarks / windowing / exactly-once, streaming SQL Materialize / RisingWave, real-time OLAP ClickHouse / Apache Druid / Apache Pinot / StarRocks / Apache Doris), (g) warehouses & query engines (Snowflake, BigQuery, Redshift, Databricks SQL, Trino / Presto, DuckDB, Polars, decoupled storage & compute, MPP), (h) data quality, testing & observability (dbt tests, Great Expectations, Soda, data contracts, Monte Carlo / data downtime, freshness / volume / schema anomaly detection, unit / integration testing of pipelines), (i) data governance, catalog & lineage (DataHub, Amundsen, OpenMetadata, Unity Catalog, column-level lineage, PII / data classification, access control, GDPR / data privacy), (j) DataOps & reliability (CI/CD for data, version control of transformations, environments, idempotent reprocessing, SLAs / SLOs for data, cost / FinOps for compute & storage), (k) data architecture paradigms (modern data stack, data lakehouse, data mesh, data fabric, decentralized vs centralized ownership), (l) the analytics engineering role (the dbt-era bridge between data engineering and analysis); N

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Interact with Azure DevOps repositories, pull requests, and APIs using the AZURE_DEVOPS_TOKEN environment variable. Use when working with code hosted on Azure DevOps or managing Azure DevOps resources.

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Expert FinOps guidance for cloud, AI, and SaaS technology spend. Covers AI cost management, agentic FinOps, GenAI capacity planning, self-hosted vs managed inference, Anthropic billing, open-weight vendor APIs (DeepSeek, Qwen, Kimi, GLM), AWS (EC2, Bedrock, SageMaker, Savings Plans, CUR), Azure (reservations, AHB, OpenAI PTUs), GCP (Vertex AI, BigQuery), OCI, on-prem and hybrid, Kubernetes cost allocation, data platforms (Databricks, Fabric F-SKUs, Snowflake), tagging governance, SaaS management (SAM, shadow IT), AI coding tools (Cursor, Claude Code, Copilot, Codex), ITAM, allocation, showback, chargeback, anomaly management, KPIs and benchmarking, forecasting, waste detection playbooks, workload onboarding and M&A, and GreenOps (cloud carbon, CSRD). Use for any technology cost or waste question in your estate - expiring commitments or RIs, NAT gateway bills, idle VMs, snapshot sprawl - and for commitment sizing, rightsizing, or connecting spend to business value. Built by OptimNow.

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Expert guidance for deep security incident and entity investigations in Google SecOps. Use when investigating cases, analyzing entities (hosts, IPs, domains, hashes, users), extracting and searching UDM events, performing asset and user timeline analysis, and detecting lateral movement across enterprise networks. Don't use for detection rule authoring or YARA-L tuning (use secops-detection-engineering), proactive hypothesis-driven hunting (use secops-hunt), initial alert triage (use secops-triage), or basic case status updates (use secops-cases).

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