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Found 14,001 Skills
Guides Site Reliability Engineering—SLI/SLO and error budgets, reliability dashboards and burn-rate alerting, production readiness reviews, capacity planning for availability, toil reduction, dependency and failure-mode analysis, release reliability (canaries, rollback criteria), and service-owner incident mitigation tied to customer impact. Use when defining or operating SLOs, measuring error budget burn, improving service reliability, running PRRs before launch, planning scalable resilient capacity, or leading technical mitigation during outages—not for CI/CD pipeline implementation (devops), incident program and paging policy design (incident-management-engineer), cloud access and patch tickets (cloud-system-administrator), load-test profiling (performance-engineer), rollout cutover strategy (deployment-strategist), or greenfield cloud build-out (cloud-engineer).
Guides actuarial work for insurance and reinsurance—pricing and rate adequacy, reserving and IBNR, loss development and triangles, mortality/morbidity and lapse assumptions, experience studies and credibility, capital and risk metrics at overview level, product design tradeoffs (life, health, P&C, annuity), and regulatory reporting concepts (NAIC, IFRS 17, Solvency II overview—not legal advice). Use when the user mentions actuary, actuarial, IBNR, loss development, reserve analysis, mortality table, pricing insurance, experience study, IFRS 17, loss ratio, combined ratio, credibility, or asks for assumption documentation and model governance for insurance products—not generic FP&A (financial-analyst), investment banking valuation (comps-analysis, dcf-model), legal policy interpretation (commercial-counsel), clinical trials, software-only implementation (senior-software-engineer), or broad GRC without actuarial models (compliance-engineer).
Guides enterprise-scale cloud architecture—multi-BU landing zones and federation, cloud Center of Excellence governance, enterprise agreement and commit strategy, org-wide FinOps and chargeback, regulated-workload patterns (residency, segmentation), hybrid integration with identity and ERP, and architecture review board standards for large organizations. Use when designing cloud at hundreds of accounts, steering CCoE policy, EA/MACC optimization, sovereign or regulated cloud placement, or executive cloud governance—not for single-product cloud designs (cloud-architect), hands-on service config (cloud-engineer), SOC 2 evidence automation (compliance-engineer), general cross-domain ADRs (senior-system-architecture), or enterprise AI copilot architecture (applied-ai-architect-commercial-enterprise), or VP-level cloud program portfolio and board narratives (vp-of-cloud).
Guides information security risk analysis—risk identification and scoring, risk registers, threat/vulnerability/control mapping, treatment recommendations (accept/mitigate/transfer/avoid), third-party and supply-chain risk framing, business impact analysis, KRIs, and risk committee or board narratives. Aligns with ISO 27005 and NIST RMF concepts without full compliance audits. Use for security risk assessment, risk register maintenance, inherent/residual risk scoring, FAIR-style quantitative framing, treatment decisions, third-party risk tiers, or executive risk reporting—not SOC alert triage (soc-analyst), pentest execution (penetration-tester, web-pentester, network-pentester), control implementation (information-security-engineer, cloud-security-engineer), GRC program and audit prep (compliance-specialist), audit evidence automation (compliance-engineer, cloud-compliance-specialist), AI model risk programs (ai-risk-governance), or adversary simulation (red-team-specialist).
Guides senior front-end software engineering—TypeScript/React/Next.js architecture, component design, client and server rendering, state and data fetching, styling and design systems, accessibility (WCAG), performance (Core Web Vitals), testing, and senior-level UI code review. Use when building or refactoring complex UIs, designing component APIs, optimizing LCP/INP/CLS, implementing accessible interactions, integrating design tokens, or reviewing front-end PRs—not for backend APIs or databases (fullstack-software-engineer, senior-fullstack-developer), design-only critiques without implementation, CI/CD (devops), or cross-service system RFCs (senior-software-engineer). For implementing screens from design specs, component states, and visual QA, use ui-software-engineer. Deep perf investigations and load/RUM analysis: performance-engineer.
This skill should be used when the user asks for markup detection, detect manipulation, image tampering, deepfake detection, document integrity, hidden markup, metadata forensics, EXIF analysis, content authenticity, synthetic media, altered image, C2PA, or provenance verification across documents, images, and video. Guides workflow-level assessment of visual tampering indicators (splicing, cloning, inconsistent lighting or shadows, compression artifacts), metadata and provenance checks (EXIF, hashes, source chain), document revision and hidden markup (tracked changes, comments, invisible text), synthetic-media and deepfake red flags, watermarking and content-credentials concepts, and structured reporting with confidence levels and explicit limitations—not training detection models (ml-research-engineer-safeguards), cryptographic watermark design (cryptographer-specialist), full digital forensics lab attribution or legal conclusions, or blockchain-only tracing unless the user scopes on-chain context.
Extract, validate, and categorize invoice data against purchase orders and GL codes
Migrates a project from Metabase static embedding to guest embeds (web components via embed.js). Use when the user wants to migrate/convert/switch/upgrade from static embedding to guest embeds, from signed embed iframes to web components, or replace /embed/ iframes with metabase-dashboard/metabase-question components.
Generates a self-contained Python experiment client that uses the ddtrace.llmobs SDK. Emits either a runnable .py script or a Jupyter .ipynb notebook matching the canonical DataDog reference notebook style. Use when the user says "generate Python experiment", "write an SDK experiment", "create a ddtrace experiment", "Python notebook experiment", "use the LLM Obs SDK", or has `ddtrace` installed and wants idiomatic SDK code.
Drizzle ORM for type-safe SQL with PostgreSQL, MySQL, and SQLite. Use when defining schemas, writing queries, managing relations, running migrations, or using drizzle-kit. Use for drizzle, orm, schema, query, migration, pgTable, relations, drizzle-kit, drizzle-zod.
Analyzes Kubernetes resource usage metrics and historical data to suggest optimal CPU and Memory requests and limits. Use to reduce cloud costs, prevent OOMKills, and improve overall cluster reliability by right-sizing your deployments.
Vector search with SurrealDB using HNSW indexes, KNN queries, and similarity scoring. Use when creating vector indexes, querying vectors with KNN distance operators, building semantic search or RAG pipelines, tuning HNSW parameters (EFC, M, M0, distance function, type), or implementing recommendation systems with SurrealDB. Triggers: HNSW, vector, embedding, KNN, cosine, euclidean, semantic search, RAG, vector::distance.