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Found 3,365 Skills
Use when writing or reviewing Jetpack Compose UI for TV, keyboard, desktop, accessibility focus, D-pad navigation, FocusRequester, focusProperties, key events, or initial focus behavior.
Controls a running iOS, iPad, or Apple Watch Simulator via the serve-sim CLI (npx serve-sim) and streams it into the host agent's preview pane. Use whenever the user wants an AI agent to view or drive an Apple Simulator — streaming to preview, taps at normalized coordinates, multi-touch gestures, hardware buttons, rotation, memory warnings, CoreAnimation debug, synthetic camera injection, media drag-drop, or managing app privacy permissions. Triggers include "serve-sim", "iOS simulator", "Apple simulator", "iPad simulator", "Apple Watch simulator", "stream the simulator", "show the simulator in preview", "view the simulator here", "open simulator in preview", "simulator gestures", "tap on the simulator", "rotate the simulator", "inject camera feed", "grant simulator permissions", "allow push notifications in the simulator", or any request to drive or display an Apple Simulator visually. Do NOT use for Android emulators, building/installing an iOS app (use xcodebuild), booting a simulator from scratch (use xcrun simctl boot), in-app React Native runtime debugging (use rn-debugger), or real iOS hardware.
Core reference for DefiLlama MCP tools. Maps DeFi questions to the correct tool call with proper parameters. Covers entity conventions, metric interpretation, stock vs flow distinctions, percentage formatting, and error recovery. Use whenever querying DeFi data — protocol TVL, token prices, chain metrics, fees, revenue, yields, stablecoins, bridges, ETFs, hacks, raises, treasuries, or institutional holdings.
Configures the analytics side of a PostHog experiment — exposure criteria (default `$feature_flag_called` vs custom exposure events), primary and secondary metrics, the supported metric types (count, sum, ratio with `math` and `math_property`, retention with `retention_window_start` and `start_handling`), multivariate user handling ("Exclude" vs "First seen variant"), and how to read results once the experiment is live. Use when the user adds or edits a primary or secondary metric (e.g. "add a secondary metric tracking 'downloaded_file' per user"), sets up a ratio metric (e.g. "revenue from purchase_completed / pageviews"), sets up a retention metric (e.g. "$pageview → uploaded_file, 7-day window"), configures custom exposure (e.g. "only count users who hit /checkout"), changes multivariate handling, or asks "who is in the analysis?", "how do I measure impact?", "is this winning?", "what's the confidence level?", or "should I ship?".
Configures the rollout shape of a PostHog experiment — the variant split (50/50, 80/20, A/B/C ratios), the overall rollout percentage that gates how many users enter the experiment, and the disambiguation when a percentage like "roll out to 25%" could mean either. Use when the user mentions a rollout percentage, variant split, or traffic distribution; gives a ratio like 60/40, 70/30, or 80/20; asks "who sees the test variant?"; wants to increase, decrease, or change the rollout or split on a draft or running experiment; weighs equal vs uneven splits; or proposes a mid-experiment split change (often an anti-pattern that needs reset or end-and-restart).
Count the Tokens consumed by the local Codex in recent time by task purpose dimension, and output a Chinese table including model and category proportions; output the Faster x2 status only when explicit session-level fields exist.
Use when you need to apply Java exception handling best practices — including using specific exception types, managing resources with try-with-resources, securing exception messages, preserving error context via exception chaining, validating inputs early with fail-fast principles, handling thread interruption correctly, documenting exceptions with @throws, enforcing logging policy, translating exceptions at API boundaries, managing retries and idempotency, enforcing timeouts, attaching suppressed exceptions, and propagating failures in async/reactive code. This should trigger for requests such as Exception handling; Use try-with-resources in Java code; Create exception chaining in Java code; Apply fail-fast validation in Java code. Part of cursor-rules-java project
Use when you need to implement or improve Java logging and observability — including selecting SLF4J with Logback/Log4j2, applying proper log levels (ERROR, WARN, INFO, DEBUG, TRACE), parameterized logging, secure logging without sensitive data exposure, environment-specific configuration, log aggregation and monitoring, or validating logging through tests. This should trigger for requests such as Improve logging; Apply logging; Refactor logging; Add logging support. Part of cursor-rules-java project
Check if the development environment is configured properly; if not, first confirm the office location (Chongqing/Beijing), identify the current operating system, system tools, package managers, and eliteforge-* skill environment variable declarations, report them categorized as missing_required, missing_conditional, optional_unset, then attempt to automatically install essential commands and complete configurations such as hosts, Git global settings, Git HTTPS, npm/pip private sources, and pipx packages. Use this skill when the user mentions "check environment configuration", "prepare development environment", "missing commands/hosts/private sources/Git configurations/package management tools/skill environment variables". Trigger threshold: Only use this skill when the user explicitly states that the current project complies with the "璀璨工坊规范" (Bright Workshop Specification) or "eliteforge specification".
Use when reviewing academic papers, proposals, experiments, claims, related work, novelty, methodology, or manuscripts as a severe but fair peer reviewer before submission.
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.
Drafts, reviews, rewrites, and coaches outcome-based OKR sets across team, department, product, or company scopes. Supports five entry modes (Guided default, One-Shot via --oneshot, Sustained Coach, Audit Only, Rewrite). Diagnoses empowered-team context and adjusts framing; refuses to fabricate baselines or targets; refuses to use OKR scores for compensation; reframes feature-delivery KRs into outcome KRs. Use when planning quarterly OKRs, translating strategy into team outcomes, reviewing draft OKRs for quality, or converting roadmap-as-OKR drafts into proper OKR sets.