Use for **any DSA question — interview prep OR day-to-day code work** — algorithm paradigms (BFS, Dijkstra, sliding window, monotonic stack, Union-Find, binary search, backtracking, topological sort, trie, DP), data structures (heap, segment tree, fenwick, trie), Java collection choice (HashMap/TreeMap, ArrayList/LinkedList, ArrayDeque/PriorityQueue, Comparator) while writing production code, graph primitives, complexity analysis, or refactoring existing code for better Big-O. Answers in Signal/Technique/Invariant/Complexity (STIC) card format; persists cards to a user-writable skill-state directory (see references/path-config.md). **Not for software design patterns** — use `design-pattern-practice`. Triggers on "classify this problem", "Java template for X", "shortest path", "HashMap vs TreeMap", "next greater element", "top K elements", "why is this loop slow", "is this O(N²)", "which collection should I use", "optimize this nested loop", "review this for algorithmic complexity".

Extends Fastly VCL with loops, functions, constants, macros, conditionals, and includes via XVCL — a VCL transpiler that compiles .xvcl files into standard VCL. Use when writing VCL for Fastly, working with .xvcl files, generating repetitive VCL (multiple backends, routing rules, headers) with loops, defining reusable VCL functions with return values, using compile-time constants instead of magic numbers, or writing any Fastly VCL configuration. XVCL syntax is not in training data so this skill is required. Also applies when writing and testing VCL locally (compile with `uvx xvcl`, test with falco), reducing VCL code duplication, splitting large VCL into modular includes, or doing any VCL development task for Fastly — even without explicitly mentioning XVCL.

Automatically validates and enforces GitHub Actions best practices for Vertex AI and Google Cloud deployments. Expert in Workload Identity Federation (WIF), Vertex AI Agent Engine deployment pipelines, security validation, and CI/CD automation. Triggers: "create github actions", "deploy vertex ai", "setup wif", "validate github workflow", "gcp deployment pipeline"

Use when working with an Aspire distributed application: operate an AppHost or resources through the Aspire CLI; start, stop, restart, or wait for resources; inspect app state, logs, traces, docs, or health; add integrations; manage secrets/config; publish/deploy or run pipeline steps; initialize an existing app; recover TypeScript `.modules`; find frontend URLs for Playwright; expose custom dashboard/resource commands; or understand Aspire AppHost APIs in C# or TypeScript. Use even if the user says AppHost, resources, dashboard, bootstrap, Playwright URL, or local distributed app workflow without naming Aspire. Do not use for non-Aspire .NET apps, container-only repos without an AppHost, or ordinary build/test tasks.

Build and deploy a Coralogix dashboard for a given service from its logs, spans, metrics, and service specs. Discovers telemetry via cx CLI commands, emits importable Coralogix JSON, verifies every PromQL and DataPrime query live through the `cx` CLI, and creates or updates dashboards via `cx dashboards create` and `cx dashboards replace`. Use whenever the user asks to create, build, generate, deploy, update, replace, or modify a Coralogix dashboard, monitoring dashboard, or observability dashboard for a service, app, or pipeline.

Kubernetes cluster, pod, node, and workload monitoring. Use when analyzing K8s health, resource optimization, pod failures, OOMKills, scheduling, or security posture. Also use for Kubernetes operational events like pod restarts, OOM events, evictions, and cluster event history. Trigger: "Kubernetes pods", "K8s cluster health", "OOMKill", "pod restarts", "container CPU", "namespace resource usage", "over-provisioned pods", "privileged containers", "pod placement", "K8s node capacity", "running containers by cluster", "workload scheduling", "pod evictions", "K8s labels and annotations", "kubernetes events", "pod restart events", "OOM events", "K8s event history". Do NOT use for explaining existing queries, product documentation questions, AWS-specific resource queries, service-level RED metrics, distributed tracing, or log analysis — use the relevant skill instead.

DAVIS problem analysis including root cause identification, impact assessment, and correlation with other telemetry. Use when querying or investigating detected problems. Trigger: "active problems", "root cause analysis", "problem impact", "affected users", "list problems", "P-12345 details", "recurring problems", "problem history", "problem trending", "blast radius", "which entity caused the problem", "problems affecting Kubernetes", "problems by service". Do NOT use for explaining existing queries, product documentation questions, generic log searching, distributed tracing, or host-level resource monitoring.

Host and process metrics including CPU, memory, disk, network, containers, and process-level telemetry. Use when analyzing infrastructure health, resource utilization, process consumption, or host discovery. Also use when building timeseries queries for host metrics that feed into analytical workflows like anomaly detection, forecasting, or seasonality analysis. Trigger: "show hosts", "CPU usage", "memory utilization", "disk space", "high CPU", "host with most free disk", "top hosts by CPU", "top processes by memory", "Linux hosts in AWS", "what databases are running", "infrastructure costs by cost center", "hosts running EOL Java", "container monitoring", "listening ports", "process resource consumption", "CPU forecast", "memory anomaly", "host seasonality". Do NOT use for explaining existing queries, product documentation questions, Kubernetes pod/workload queries (use dt-obs-kubernetes), AWS cloud resource inventory (use dt-obs-aws), or service-level metrics (use dt-obs-services).

Use when writing or reviewing Python code in this repo that calls Deepgram Text Intelligence / Read (`/v1/read`) for sentiment, summarization, topic detection, and intent recognition on text input. Covers `client.read.v1.text.analyze(...)` with body `text` or `url`. Use `deepgram-python-audio-intelligence` when the source is audio instead of text. Triggers include "read API", "text intelligence", "analyze text", "sentiment", "summarize text", "topics", "intents", "read.v1".

Use when writing or reviewing JavaScript/TypeScript in this repo that calls Deepgram Speech-to-Text v1 (`/v1/listen`) for prerecorded or live audio transcription. Covers `client.listen.v1.media.transcribeUrl` / `transcribeFile` (REST) plus `client.listen.v1.createConnection()` / `connect()` (WebSocket). Use `deepgram-js-audio-intelligence` for summarize/sentiment/topics/diarize overlays, `deepgram-js-conversational-stt` for Flux turn-taking on `/v2/listen`, and `deepgram-js-voice-agent` for full-duplex assistants. Triggers include "transcribe", "speech to text", "STT", "listen.v1", "nova-3", "live transcription", and "websocket transcription".

Enrich an IOC (IP, domain, hash, URL) with threat intelligence. Use when you need to look up reputation and context for an indicator using GTI and SIEM. Returns threat intel findings, SIEM entity summary, and IOC match status.

Orchestrate Xcode build optimization by benchmarking first, running the specialist analysis skills, prioritizing findings, requesting explicit approval, delegating approved fixes to xcode-build-fixer, and re-benchmarking after changes. Use when a developer wants an end-to-end build optimization workflow, asks to speed up Xcode builds, wants a full build audit, or needs a recommend-first optimization pass covering compilation, project settings, and packages.

Apply approved Xcode build optimization changes following best practices, then re-benchmark to verify improvement. Use when a developer has an approved optimization plan from xcode-build-orchestrator, wants to apply specific build fixes, needs help implementing build setting changes, script phase guards, source-level compilation fixes, or SPM restructuring that was recommended by an analysis skill.

Benchmark Xcode clean and incremental builds with repeatable inputs, timing summaries, and timestamped `.build-benchmark/` artifacts. Use when a developer wants a baseline, wants to compare before and after changes, asks to measure build performance, mentions build times, build duration, how long builds take, or wants to know if builds got faster or slower.

Use when you need to use Spring Data JDBC with Java records — including entity design with records, repository pattern, immutable updates, aggregate relationships, custom queries, transaction management, and avoiding N+1 problems. This should trigger for requests such as Review Java code for Spring Data JDBC; Apply best practices for Spring Data JDBC in Java code. Part of cursor-rules-java project

Append a structured learning entry to AGENTS_LEARNING.md whenever an AI agent makes a mistake. Auto-activates as a composite skill when: a pre-write skill violation is detected and auto-fixed, or when the session retrospective finds a correction loop. Also triggers directly when the user corrects the AI mid-session. Use when: mistake, wrong, redo, that's not right, correction, my bad, fix that error, I made a mistake, agent error, learning log, log mistake, AGENTS_LEARNING.md

Implement ViewBinding, RecyclerView, and XML layouts correctly on Android. Use when working with XML layouts, ViewBinding, or RecyclerView adapters in legacy Android projects.

Build standalone Angular components with Signals inputs, OnPush change detection, Control Flow, and Smart/Dumb patterns. Use when building standalone Angular components, implementing @if/@for control flow, applying OnPush change detection, or implementing Signals in Angular components.

Implement application state with Angular Signals, computed derivations, and NgRx Signal Store. Use when implementing reactive state with signal(), computed(), effect(), or @ngrx/signals in Angular.

Use when you need to refactor Java code to adopt modern Java features (Java 8+) — including migrating anonymous classes to lambdas, replacing Iterator loops with Stream API, adopting Optional for null safety, switching from legacy Date/Calendar to java.time, using collection factory methods, applying text blocks, var inference, or leveraging Java 25 features like flexible constructor bodies and module import declarations. This should trigger for requests such as Review Java code for modern Java development; Apply best practices for modern Java development in Java code. Part of cursor-rules-java project