Total 59,012 skills
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This skill should be used when the user asks to "add background processing", "cache this data", "run this async", "handle concurrent requests", "manage state across requests", "process jobs from a queue", "this GenServer is slow", or mentions GenServer, Supervisor, Agent, Task, Registry, DynamicSupervisor, handle_call, handle_cast, supervision trees, fault tolerance, "let it crash", or choosing between Broadway and Oban.
Manage long-session context to prevent drift and degradation. Strategies for proactive summarization, branch isolation, and /clear decisions. Invoke when context feels heavy, when accuracy starts slipping, or proactively after a major phase boundary. Addresses the
Query VictoriaTraces via curl using the Jaeger-compatible API. Use when discovering traced services and operations, searching traces by service/operation/duration/tags, retrieving traces by ID, or mapping service dependencies. Triggers on: trace queries, span search, trace ID lookup, service discovery, operation discovery, service dependencies, distributed tracing, Jaeger API.
Unified review skill — auto-detects plan or code, assembles the right panel, runs a bounded review-fix loop with severity gating. Use when a plan or implementation needs review.
Automatically generate standardized comments for Vue 2 Single-File Components (.vue). Parse the three blocks of template, script, and style, add structured comments according to the agreed format, without modifying any code logic. Trigger scenarios: Users request to add comments, supplement document comments for components, and interpret Vue 2 component structure.
Content generation skill for the Orbitant engineering blog. Activates when creating a blog post from raw input (transcript, notes, or draft). Produces a structured, SEO-optimised article in Spanish that matches Orbitant's tone, editorial standards, and content cluster strategy. Use this skill whenever someone provides raw material and asks to turn it into a publishable blog post for the Orbitant blog.
Research Google Trends search-intent signals for topic discovery, keyword momentum, regional interest, and rising queries without treating search trends as the same thing as platform content heat or marketplace demand.
Format values for display using the FormatStyle protocol and its concrete types. Use when formatting numbers (integers, floating-point, decimals), currencies, percentages, dates, date ranges, relative dates, durations (Duration.TimeFormatStyle, Duration.UnitsFormatStyle), measurements, person names (PersonNameComponents.FormatStyle), byte counts (ByteCountFormatStyle), lists (ListFormatStyle), and URLs (URL.FormatStyle). Also covers creating custom FormatStyle conformances and replacing legacy Formatter subclasses. FormatStyle is available iOS 15+; Duration styles require iOS 16+.
Apply Benjamin Graham's value investing framework to evaluate stocks, portfolio allocation, and investment vs. speculation decisions. Trigger on: "Is this stock worth buying?", "Is this investment or speculation?", "How should I allocate my portfolio?", "Is this company a good value?", "should I sell in a downturn?", "evaluate this stock for a defensive investor".
Background knowledge for droid-control workflows -- not invoked directly. Droid CLI target patterns, shortcuts, modes, and launch helpers.
Verify that a developer-run feature behaved correctly by analyzing HTTP traffic captured by Fiddler Everywhere. Always use this skill when a developer asks whether their feature's HTTP calls completed correctly, wants to see what requests a feature made, needs to debug a failed API call, is checking traffic after running a feature, wants to confirm what each endpoint returned, or asks whether anything in the traffic looks wrong — even if they don't use the word "verify" or "Fiddler". Summarizes the capture by endpoint and flags likely issues such as failed calls, missing follow-up requests, retries, auth failures, timeouts, and suspicious status-code patterns. Requires Fiddler Everywhere to be running with its MCP server enabled.
Execute tasks through competitive multi-agent generation, meta-judge evaluation specification, multi-judge evaluation, and evidence-based synthesis