DevOps skills

Design metacognitive checkpoints that prevent AI-assisted learning from bypassing genuine understanding. Use when students use AI tools and may overestimate their own comprehension.

The English summary is being prepared. Showing the original description.

Migrate Terraform provider resources and data sources from Plugin SDKv2 to the Plugin Framework: muxing both plugins in one provider (terraform-plugin-mux, tf5to6server), per-resource migration workflow, SDKv2-to-Framework schema mapping (ForceNew, ValidateFunc, DiffSuppressFunc, Default, Timeouts, blocks), null-vs-zero-value behavioral traps, and state-compatibility verification. Use when converting or translating SDKv2 resources to the Framework, setting up a muxed provider server, deciding whether a resource should be migrated at all, or debugging plan diffs and state errors that appeared after a migration.

The English summary is being prepared. Showing the original description.

Build Windows images with Packer using WinRM communicator and PowerShell provisioners. Use when creating Windows AMIs, Azure images, or VMware templates.

The English summary is being prepared. Showing the original description.

Build Amazon Machine Images (AMIs) with Packer using the amazon-ebs builder. Use when creating custom AMIs for EC2 instances.

The English summary is being prepared. Showing the original description.

Create, update, and review Terraform provider documentation for Terraform Registry using HashiCorp-recommended patterns, tfplugindocs templates, and schema descriptions. Use when adding or changing provider configuration, resources, data sources, ephemeral resources, list resources, functions, actions, or guides; when validating generated docs; and when troubleshooting missing or incorrect Registry documentation.

The English summary is being prepared. Showing the original description.

Azure Verified Modules (AVM) requirements and best practices for developing certified Azure Terraform modules. Use when creating or reviewing Azure modules that need AVM certification.

The English summary is being prepared. Showing the original description.

Use this when scaffolding a new Terraform provider with the Plugin Framework: workspace layout, go module setup, provider server main.go, and a provider.go with schema and Configure. Also use when a user wants to start building a provider for a new API or asks how to begin a terraform-provider-* project.

The English summary is being prepared. Showing the original description.

Implement Terraform provider ephemeral resources with the Plugin Framework: the Open/Renew/Close lifecycle, ephemeral schema design, registration via EphemeralResources, renewal for expiring credentials, and how ephemeral values flow into write-only attributes and provider configuration. Use when adding an ephemeral resource, exposing secrets/tokens/certificates that must never persist in state or plan, deciding between an ephemeral resource and a data source, or wiring short-lived credentials from one provider into another.

The English summary is being prepared. Showing the original description.

Generate Terraform HCL code following HashiCorp's official style conventions and best practices. Use when writing, reviewing, or generating Terraform configurations.

The English summary is being prepared. Showing the original description.

Comprehensive guide for working with HashiCorp Terraform Stacks. Use when creating, modifying, or validating Terraform Stack configurations (.tfcomponent.hcl, .tfdeploy.hcl files), working with stack components and deployments from local modules, public registry, or private registry sources, managing multi-region or multi-environment infrastructure, or troubleshooting Terraform Stacks syntax and structure.

The English summary is being prepared. Showing the original description.

Implement Terraform Provider actions using the Plugin Framework. Use when developing imperative operations that execute at lifecycle events (before/after create, update, destroy).

The English summary is being prepared. Showing the original description.

Build Azure managed images and Azure Compute Gallery images with Packer. Use when creating custom images for Azure VMs.

The English summary is being prepared. Showing the original description.

Discover existing cloud resources using Terraform Search queries and bulk import them into Terraform management. Use when bringing unmanaged infrastructure under Terraform control, auditing cloud resources, or migrating to IaC.

The English summary is being prepared. Showing the original description.

Write, test, or convert Terraform Policy files (.policy.hcl, .policytest.hcl, Sentinel→tfpolicy). Triggers: policy.hcl, policytest, convert sentinel, tfpolicy, write a policy.

The English summary is being prepared. Showing the original description.

Expert Vietnam Personal Data Protection Law (PDPL) compliance advisor for Law No. 91/2025/QH15 and implementing Decree 356/2025/ND-CP (effective January 1, 2026). Use this skill for gap analysis against the Vietnam PDPL, data subject rights fulfilment workflows, cross-border data transfer impact assessments, privacy notices and internal policies, breach notification procedures, sector-specific obligations (finance, AI, cloud, blockchain), and DPO qualification reviews. Trigger whenever a user mentions Vietnam data privacy, VN-PDPL, Nghị định 356, Vietnamese personal data, or cross-border transfers involving Vietnamese citizens' data.

The English summary is being prepared. Showing the original description.

Assess, report, and manage serious incidents involving high-risk AI systems under Article 73 EU AI Act. Covers incident qualification, deadline buckets (2/10/15 days), authority notification, deployer duties (Art. 26(5)), cross-regulation mapping (GDPR/NIS2/MDR), corrective measures, and DACH-specific routing. Use when asked to evaluate whether an AI incident is reportable, draft an Article 73 notification, identify the right authority, or build an AI incident response process.

The English summary is being prepared. Showing the original description.

Assess whether Government of India approval is required for foreign investment in an Indian company under Foreign Exchange Management Act, 1999 and the Non-Debt Instruments Rules, 2019. The skill systematically gathers transaction details, evaluates sectoral entry routes and caps, assesses land border country restrictions under applicable laws, and delivers a preliminary compliance note. Produces clear guidance on whether the investment falls within Automatic Route or requires Government approval.

The English summary is being prepared. Showing the original description.

End-to-end external local counsel lifecycle management for multi-jurisdiction legal matters. LC selection criteria and capability assessment, engagement setup and instruction design, performance monitoring and check-in cadence, scope enforcement, and relationship escalation. Use when selecting local counsel for a jurisdiction, designing LC instructions, managing the LC check-in rhythm, enforcing scope boundaries when LC signals overreach, or escalating a performance or relationship issue beyond the matter team. Trigger on: 'which LC should we use', 'LC instruction', 'brief the local counsel', 'LC hasn't responded', 'LC is going off scope', 'LC scope dispute', 'confirm scope with LC', 'LC check-in', 'LC is slow', 'monitor the LC network', 'LC engagement letter', 'LC selection', 'what should we tell the local counsel', 'LC onboarding', 'LC performance issue', 'LC relationship problem'.

The English summary is being prepared. Showing the original description.

Determines the organization's role (provider, deployer, importer, distributor, or quasi-provider) and assesses Art. 25 quasi-provider risk of the EU AI Act. This skill should be used when the user asks to "determine AI Act roles", "check if we are provider or deployer", "assess quasi-provider status", "check Art. 25 substantial modification", "check value chain responsibilities", or mentions "Betreiber", "Anbieter", "wesentliche Veränderung", or finetuning implications under the AI Act.

The English summary is being prepared. Showing the original description.

Classify AI systems under the EU AI Act (Regulation (EU) 2024/1689) and determine compliance obligations. Use when asked to assess AI risk level, check if an AI system is prohibited, determine high-risk status, identify GPAI model obligations, map provider/deployer responsibilities, or build an AI Act compliance roadmap. Covers the full classification decision tree (Prohibited → High-Risk → Limited → Minimal → GPAI), obligations by role (provider, deployer, importer, distributor), compliance timelines, and DACH-specific considerations (German works council, BaFin, BSI, BNetzA). Triggers on phrases like "classify this AI system", "is this high-risk under the AI Act", "AI Act risk assessment", "EU AI Act compliance", "prohibited AI practice", "GPAI obligations", "AI Act timeline".

The English summary is being prepared. Showing the original description.

EU AI Act (Regulation (EU) 2024/1689) compliance advisor — risk classification across all four tiers, all 9 prohibited practices (Art. 5, including the nudification/CSAM prohibition from Dec 2, 2026), all 8 Annex III high-risk use case areas, provider and deployer obligations (Arts. 9–17, 26), GPAI model obligations including the July 2025 Code of Practice (Arts. 51–55), conformity assessment and CE marking (Arts. 43–48), EU AI database registration, Art. 50 transparency (chatbots, synthetic media, AI-generated content), governance (AI Office, AI Board), penalties (Art. 99), confirmed phase-in timeline (Digital Omnibus adopted June 29, 2026: Annex III deferred to Dec 2, 2027; Annex I to Aug 2, 2028), and cross-framework mapping to ISO 42001, NIST AI RMF, and GDPR. Use for any EU AI regulation, AI system classification, or AI compliance question. Current as of July 2026. GPAI enforcement powers activate August 2, 2026.

The English summary is being prepared. Showing the original description.

Assess and operationalize implementation readiness for high-risk AI systems under the EU AI Act Annex III, including provider and deployer obligations, conformity assessment, post-market monitoring, and EU database registration. Use when users say things like “we classified this as high-risk, what now?”, “build an EU AI Act readiness plan”, “assess our Annex III compliance gaps”, “what do providers/deployers of high-risk AI need to implement?”, “prepare for conformity assessment”, or “create a high-risk AI implementation roadmap.”

The English summary is being prepared. Showing the original description.

Assesses which of the Art. 50(1)-(5) transparency obligations of the EU AI Act apply to a given AI system's provider or deployer, grounded in the final Code of Practice on Transparency of AI-Generated Content (June 2026) and the Commission's draft Art. 50 Guidelines. Covers AI-chatbot disclosure, deepfake and synthetic-content marking/watermarking, emotion-recognition and biometric-categorisation notices, the machine-readable marking duty, the obviousness exceptions, and the implementation timeline. Outputs a formal mini-report plus a per-obligation compliance checklist with gap flags. For breadth-first tier triage use the EU AI Act System Classifier; for raw Art. 50 text and Q&A use the EU AI Act Knowledge Base; for the full role x tier matrix use the EU AI Act Obligations Mapper.

The English summary is being prepared. Showing the original description.

Assess whether a Fundamental Rights Impact Assessment (FRIA) is required under Article 27 EU AI Act, and structure or draft that assessment for a specific high-risk AI deployment. Covers deployer scope gating (public bodies and private entities providing public services), affected group mapping, Charter rights analysis, proportionality, safeguards evaluation, residual risk, DPIA/FRIA cross-referencing under the amended Article 27(4), the unconditional notification duty under Article 27(3), and DACH-specific considerations. Use when asked about FRIA obligations, Article 27 scope, fundamental rights and AI, or deployer assessment duties.

The English summary is being prepared. Showing the original description.