Loading...
Loading...
Found 3,111 Skills
Feature-level UX audit for React/Next.js code. Catches what Lighthouse, axe, ESLint, and Storybook miss — state coverage gaps (missing loading/empty/error), form data loss on validation, broken focus management, optimistic UI without rollback, skeleton-induced layout shift, vague microcopy, and 25+ other modern frontend UX bugs. Diff-aware (audits changed files only) and produces a 3-tier ship-readiness verdict (release-blocker / fix-this-sprint / backlog) grouped by surface, with concrete fixes using modern React 19 APIs (useActionState, useFormStatus, useOptimistic, useTransition, Suspense). Use before merging a frontend PR, before shipping a feature, or when asked "is this checkout/onboarding/dashboard ready?", "review this PR for UX bugs", "audit this component", "what would break in production?", "is this ready to ship?"
Parse and analyze email headers to trace the origin of phishing emails, verify sender authenticity, and identify spoofing through SPF, DKIM, and DMARC validation.
Write the canonical engineering record of a fixed bug — root cause, mechanism, fix, validation, and how it slipped through. Engineer-audience, code identifiers welcome. Use after a debug session lands a fix, before closing the ticket. Trigger on /post-mortem, when the user says "write the post-mortem / postmortem / RCA / root cause analysis", "document this fix", "write up the root cause", "close out this bug with a writeup", or hands you a fixed-and-validated bug and asks for the writeup.
Guides hands-on actuarial analyst work for insurance, reinsurance, and pension—reserving and loss development (IBNR, triangles, chain-ladder diagnostics), pricing and rate indication support (experience, trend, credibility, basic GLM at spec level), data validation and model I/O review, reporting packs and workpapers, assumption application under actuary direction, and statutory tie-outs at analyst depth. Use when the user mentions actuarial analyst, loss development, IBNR, reserve analysis, rate indication, pricing support, actuarial workpaper, triangle analysis, credibility, experience study, actuarial reporting, or reserve roll-forward—not actuary sign-off (actuary), consulting engagements (actuarial-consulting), assumption governance (assumption-setting), ALM strategy (asset-liability-management), P&C legal depth (property-casualty-insurance), charts only (data-visualization), or ETL-only pipelines (data-scrubbing).
Guides secure software delivery and DevSecOps for cleared/classified or high-side programs—disconnected or air-gapped CI/CD, artifact promotion across classification boundaries (conceptual), SBOM/signing/ provenance, SAST/DAST/secrets/IaC/container gates, supply-chain controls, STIG/CIS deploy baselines, IaC for classified landing zones, cleared developer workstations, build/deploy audit logging, and ATO/RMF pipeline evidence (not SSP ownership). Use for classified DevSecOps, cleared pipeline, high-side CI/CD, air-gapped build, cross-domain release, classified software delivery, STIG pipeline, ATO evidence CI, SBOM classified, secure software factory—not portfolio cyber governance (classified-cyber-security-senior-manager), ISSO/SSP (information-systems-security-officer-classified-specialist), commercial-only DevSecOps (devsecops), general DevOps (devops), build-only validation (build-validator), pentest (penetration-tester), or enterprise GRC-only (compliance-specialist).
Use this skill whenever the user wants to integrate Loops from application code, backend services, webhook handlers, or server-side automation. This includes the Loops HTTP API and official SDKs for server-side contact, contact-property, mailing-list, event, API-key-validation, and transactional-email workflows. Trigger on phrases like "Loops API", "Loops SDK", "send a Loops event from my app", "add a contact to Loops in a webhook", "send a transactional email from backend code", or any time the user wants to integrate Loops into their app, backend, webhook, or automation. Do not trigger for CLI or shell-only requests.
Use when an SGLang, vLLM, or TensorRT-LLM serving/model optimization task needs prior model-family PR evidence. Query and read the PR-driven history docs under model-pr-optimization-history before choosing source paths, fast paths, kernel/fusion ideas, regression risks, or validation lanes.
Use when user explicitly asks Flink/Ververica/Realtime Compute Console workspace operations: 草稿(draft), SQL校验/执行, 部署(deployment), 作业(job), Session Cluster, namespace, 表(table), 成员(member), 变量(variable), 或 checkpoint timeout 诊断, especially with workspace/deployment/job IDs (w-*, d-*, j-*, sc-*, draft-*). Also use when prompt asks to test/verify Flink Console lifecycle flow, safety guardrails, or parameter validation for these operations. This includes prompts such as create draft, deploy draft, list deployments, start/stop job, create/list session cluster, get tables, list variables. Also use when prompt explicitly asks to run `python scripts/flink_ververica_ops.py` for Flink Console workspace operations. Do not trigger for unrelated "workspace" contexts or generic cloud/platform tasks (ECS, OSS, RDS, Kafka, Spark, Kubernetes, billing, weather). Do not trigger for Flink instance lifecycle operations (create/scale/delete/renew); those belong to alibabacloud-flink-instance-manage.
Pinia Colada data fetching for Vue/Nuxt with useQuery, useMutation. Use for async state, query cache, SSR, or encountering invalidation, hydration, TanStack Vue Query migration errors.
Build, refactor, review, and debug native Apple-platform software in Swift. Use when working on `.swift` files, SwiftUI views, Observation-based state, `@Bindable` and binding flow, SwiftData-backed UI, scenes and windows, search/navigation structures, UIKit/AppKit interop, Liquid Glass adoption, macOS-native UX, or SwiftUI performance/accessibility. Trigger on requests to create or polish iOS, iPadOS, macOS, or visionOS features; clean up SwiftUI view structure; diagnose jank or invalidation storms; review app quality; or make a feature feel like a good Apple-platform citizen.
Guideline for designing, implementing, and verifying secure Python applications following OWASP Top 10 best practices. Use when the user wants to: (1) review Python code for security vulnerabilities, (2) design a secure Python application architecture, (3) implement security features (authentication, authorization, cryptography, input validation), (4) audit Python dependencies for known vulnerabilities, (5) create security checklists or verification plans, (6) fix security bugs or harden existing Python code, (7) set up security testing and static analysis (bandit, safety, semgrep), or (8) handle any Python security concern including injection prevention, secure deserialization, SSRF protection, secrets management, and secure deployment.
Adaptive multi-agent framework for automated data science tasks with planning, execution, and validation