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Found 1,323 Skills
Flux CD and Flux Operator expert — answers questions and generates schema-validated YAML for all Flux CRDs (not repo auditing or live cluster debugging). Use when users ask about Flux concepts, want manifests for HelmRelease, Kustomization, GitRepository, OCIRepository, ResourceSet, FluxInstance, or any Flux resource, or need guidance on GitOps repository structure, multi-tenancy, OCI-based delivery, image tag automation, drift detection, preview environments, notifications, or the Flux Web UI and MCP Server. Whenever users mention FluxCD, Flux Operator, or any Flux CRD in a question or manifest generation context, always use this skill.
k6 performance and load testing. Covers writing test scripts in JavaScript/TypeScript, all test types (load/stress/spike/soak/smoke/breakpoint), thresholds, checks, scenarios, executors, extensions, result analysis, k6 Cloud execution, and CI/CD integration. Use when writing k6 tests, debugging test failures, setting up load testing pipelines, choosing executors/scenarios, or interpreting k6 results.
129 practical Oracle Database and Oracle Container Registry reference guides covering SQL/PL/SQL development, performance tuning (AWR, ASH, explain plan, indexes, wait events, memory), security (TDE, VPD, auditing, network), administration (RMAN, Data Guard, undo/redo, users), monitoring, architecture (RAC, CDB/PDB, Exadata, In-Memory, OCI), DevOps (Liquibase, Flyway, utPLSQL, EBR), migrations from Postgres/MySQL/SQL Server/MongoDB/Snowflake/Redshift/DB2, PL/SQL development (packages, cursors, collections, unit testing, debugging), Oracle features (AQ, DBMS_SCHEDULER, materialized views, APEX), SQLcl (basics, scripting, Liquibase, MCP server, CI/CD), ORDS (architecture, authentication, AutoREST, REST API design, PL/SQL gateway), and Oracle Container Registry images. Use for any Oracle DB question, ORA- errors, DBMS_ packages, v$ views, Oracle tooling, ORDS REST APIs, SQLcl commands, or Oracle container images. Always consult this skill before answering Oracle-specific questions.
Doctor Strange — forward mental simulation via parallel universe subagents. Walks through how a future event might unfold step by step, like a human mentally rehearsing a scenario. Stores simulations as persistent memory for later recall. TRIGGER when: user explicitly asks to simulate / rehearse / play out a scenario; user says "推演", "模拟", "预演", "imagine", "what if", "run through", "play this out", "what could go wrong"; user faces a high-stakes upcoming decision and is uncertain how it will unfold. DO NOT TRIGGER when: user wants factual lookup or research; user wants analysis of a past event (use regular memory); user wants a simple recommendation without simulation; user is debugging code or doing technical work unrelated to decision-making. Three modes: SIMULATE (run a new forward simulation), RECALL (surface past simulations as soft priors), MANAGE (list/void/re-run stored simulations).
Use when building custom agent backends, implementing the AG-UI protocol, debugging streaming issues, or understanding how agents communicate with frontends. Covers event types, SSE transport, AbstractAgent/HttpAgent patterns, state synchronization, tool calls, and human-in-the-loop flows.
Use when debugging TypeScript/JavaScript bugs by tracing call chains, understanding unfamiliar codebases quickly, making architectural decisions, or reviewing code quality. Extract function signatures and JSDoc without full file reads, trace call hierarchies up/down, detect code smells, and follow data flow. Triggers on debugging, understanding codebase, architectural analysis, signature extraction, call tracing.
Control a Chrome browser session through the chrome-devtools-axi CLI - navigate, snapshot, click, fill forms, run JavaScript, inspect console and network, take screenshots, audit performance. Use whenever a task needs a real browser: opening or testing a web page, clicking through a flow, extracting page content, or debugging a website.
Debug Flutter applications systematically with this comprehensive troubleshooting skill. Covers RenderFlex overflow errors, setState() after dispose() issues, null check operator failures, platform channel problems, build context errors, and hot reload failures. Provides structured four-phase debugging methodology with Flutter DevTools, widget inspector, performance profiling, and platform-specific debugging for Android, iOS, and web targets.
Debug Angular applications systematically with expert-level diagnostic techniques. This skill provides comprehensive guidance for troubleshooting dependency injection errors, change detection issues (NG0100), RxJS subscription leaks, lazy loading failures, zone.js problems, and common Angular runtime errors. Includes structured four-phase debugging methodology, Angular DevTools usage, console debugging utilities (ng.probe), and performance profiling strategies for modern Angular applications.
Debug Docker containers, images, and infrastructure with systematic diagnostic techniques. This skill provides comprehensive guidance for troubleshooting container exit codes, OOM kills, image build failures, networking issues, volume mount problems, and permission errors. Covers four-phase debugging methodology from quick assessment to deep analysis, essential Docker commands, debug container techniques for minimal images, and platform-specific troubleshooting for Windows, Mac, and Linux.
Debug Flask applications systematically with this comprehensive troubleshooting skill. Covers routing errors (404/405), Jinja2 template issues, application context problems, SQLAlchemy session management, blueprint registration failures, and circular import resolution. Provides structured four-phase debugging methodology with Flask-specific tools including Werkzeug debugger, Flask-DebugToolbar, and Flask shell for interactive investigation.
Debug TensorFlow and Keras issues systematically. This skill helps diagnose and resolve machine learning problems including tensor shape mismatches, GPU/CUDA detection failures, out-of-memory errors, NaN/Inf values in loss functions, vanishing/exploding gradients, SavedModel loading errors, and data pipeline bottlenecks. Provides tf.debugging assertions, TensorBoard profiling, eager execution debugging, and version compatibility guidance.