Skills
100,928 packaged capabilities and playbooks for agents. Install any of them with one command.
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Media3 / CameraX reference for Android app development (Kotlin). androidx.media3, androidx.camera. ExoPlayer, HLS / DASH / RTSP / SmoothStreaming, HlsInterstitialsAdsLoader, CMCD, MediaSession, MediaSessionService, MediaLibraryService, DRM, Compose UI (PlayerSurface), ProcessCameraProvider, CameraSelector, ImageCapture, ImageAnalysis, VideoCapture, CameraInfo, CameraX Extensions, Camera2 Interop, Camera1 migration.
Prevent, detect, and repair AI coding slop and dirty engineering in repositories. Use for planning features, writing code, changing tests, reviewing pull requests, refactoring, hardening CI, debugging regressions, or auditing agent-generated changes. Enforces behavioral contracts, focused diffs, test integrity, repo conventions, security boundaries, and evidence-based completion.
This skill should be used when the user asks to "test API security", "fuzz APIs", "find IDOR vulnerabilities", "test REST API", "test GraphQL", "API penetration testing", "bug bounty API testing", or needs guidance on API security assessment techniques.
Use when building, restyling, critiquing, or making any interface feel Apple-grade / premium / Cupertino-quality, or when you need Apple's design philosophy (Human Interface Guidelines — clarity, deference, depth), the 2025 Liquid Glass design language, or a map into deep Apple references. This is the HUB; route to apple-design-foundations/-materials/-motion/-os/-web/-backend/-tactics for specifics. Keywords: apple design, HIG, human interface guidelines, design philosophy, clarity deference depth, liquid glass, iOS 26, macOS Tahoe, visionOS, apple-grade, premium UI, cupertino, design system, make it look apple.
Draft, critique, and revise concise cold emails to professors for PhD applications, research internships, RA opportunities, lab rotations, or prospective-supervisor outreach. Use this skill whenever the user wants to contact a professor, ask about PhD openings, request a meeting, introduce their research background, mention a paper, follow up politely, or convert professor-fit notes into an email. This skill should trigger even if the user says "email a PI", "message a potential advisor", "reach out to faculty", or "cold mail" rather than "cold email".
Extracts key architectural decisions from technical-requirements.yaml and formalizes them as individual ADR markdown files in an adrs/ directory. Each ADR captures context, the decision made, alternatives considered, and consequences — creating a durable record of why the system is built the way it is.
Archive a completed spec — verify every task completed, QA passed, and indexed references are self-contained, then write <slug>.md under the resolved archive root (<spec-root>/_archived/, or docs/history/specs/ for the built-in docs/specs root) and remove the Spec folder, which stays in Git at the record's source_revision. Runs automatically at the end of a Roundfix Spec Run after a QA pass, or whenever the user asks to archive a spec.
Organize a Figma COMPONENT_SET's variants into a clean, labeled grid — rows and columns derived from the variant properties, with row labels on the left, column headers on top, and a titled white container. Use when a variant set is a messy pile and you want a presentable, documentation-ready layout — triggers: 'arrange my variants in a grid', 'organize this component set', 'lay out the variants with labels', 'make a variant matrix', 'clean up my component set layout', 'add row/column headers to my variants'. Picks the last property (usually State) as columns and the rest as rows by default. NOT something the native MCP's read-only tools do — this writes a new organized layout to the canvas.
Use this skill to verify Compose layout measurements from a UI test using `assertWidthIsEqualTo`, `assertHeightIsEqualTo`, `assertWidthIsAtLeast`, `assertHeightIsAtLeast`, `assertTouchWidthIsEqualTo`, `assertTouchHeightIsEqualTo`, `assertPositionInRootIsEqualTo`, `assertTopPositionInRootIsEqualTo`, `assertLeftPositionInRootIsEqualTo`, plus read helpers `getUnclippedBoundsInRoot`, `getBoundsInRoot`, `getAlignmentLinePosition`, `getFirstLinkBounds`, and the underlying `Dp.assertIsEqualTo(expected, subject, tolerance = Dp(.5f))`. Covers the half-dp default tolerance, the unclipped vs clipped distinction, the canonical "compute padding from two unclipped rects" pattern, and minimum-touch-target assertions like `assertHeightIsAtLeast(MinHeight + 1.dp)`. Use when the developer wants to assert sizes, padding, alignment, position in dp, or asks about `getUnclippedBoundsInRoot`, `DpRect`, touch-target size, or compares widths in pixels. If the developer is comparing layout dimensions from a test, use this skill.
Manage database schemas, migrations, data scripts, and Atlas Cloud operations with the Atlas CLI. Use for generating or applying migrations, diffing, linting, validating, or testing schemas; working with atlas.hcl, schema.hcl, or ORM schemas (GORM, Drizzle, SQLAlchemy, Django, Ent, Sequelize, TypeORM, Prisma); running data backfills, purges, or reports with atlas script; or answering questions about Atlas Cloud, including synced, pending, or failed databases, recent or failed deployments, what is awaiting deployment, registry repos, and pending plan approvals.
When the user wants to understand their YouTube audience, mine viewer psychology, analyze demographics, or find content-market fit signals. Also use when the user says 'who is my audience,' 'audience research,' 'viewer psychology,' 'what does my audience want,' 'comment analysis,' 'demographic insights,' 'content-market fit,' 'understand my viewers,' 'audience persona.' For channel-level health check, see channel-audit. For generating ideas from audience insights, see idea-generation.
Find every implicit and explicit state machine in a codebase, model each one formally, and report every bug the model shows and the code confirms — a bad state that can be reached, a forbidden transition, a state with no way out — with its fix and an offer to turn the findings into Tickets. Changes no code. Use when the user asks to audit state machines, find implicit state machines, check status or lifecycle logic across an app, or find status or lifecycle bugs that span several files.
Generate or update Laravel plugin REST APIs in AureusERP for any module. Use when implementing new API resources or refactoring existing endpoints to match shared project conventions for routes, controllers, requests, resources, policies, Spatie QueryBuilder filtering/includes/sorting, soft-delete restore/force endpoints, and Scribe attributes/documentation.
Use auto-run-agent to automatically analyze, evaluate, design, and optimize a target project. The full workflow includes: explore the project's current state → identify problems → design a task list → create the runner environment → start autonomous execution. Suitable for any project that needs batch optimization.
AUTOSAR BSW expert. Defaults to Classic AUTOSAR (BSW/MCAL/RTE, static config, C, AUTOSAR OS) and operates in six modes: (1) BSW configuration — Com, NvM, Dem, Dcm, Os, MemIf with dependency chain and EB Tresos / DaVinci container paths; (2) ARXML debugging — classify, locate, and fix consistency errors with a corrected fragment and prevention rule; (3) RTE generation troubleshooting — diagnose generator failures across pre-gen, contract, implementation, and post-gen build phases; (4) COM stack debugging — layer-walk CanDrv → CanIf → PduR → Com → RTE for missing, wrong, stale, or intermittent CAN signals; (5) Boot, NVM & power — EcuM/BswM startup and shutdown, bootloader / UDS reprogramming, NvM/Fee/Ea storage, sleep/wakeup, partial networking; (6) Communication protocol — CAN / CAN FD, LIN, CanTp, PduR gateway, ComM/Nm, UDS (ISO 14229), SOME/IP, DoIP. Handles Adaptive AUTOSAR (ara:: clusters) when the input names ara::com, ara::exec, POSIX, or manifests, plus legacy bring-up behind MCAL/CDD interfaces.
Expert knowledge for Azure Content Understanding in Foundry Tools development, including troubleshooting, best practices, decision-making, architecture and design patterns, limits and quotas, security, configuration, and integrations and coding patterns. Use when building Content Understanding analyzers, RAG document flows, agent integrations, RPA workflows, or REST/SDK apps, and for other Azure Content Understanding in Foundry Tools development tasks. Not for Azure Speech in Foundry Tools (use azure-speech), Azure AI Search (use azure-cognitive-search), Azure AI Vision (use azure-ai-vision), or Azure AI Document Intelligence (use azure-document-intelligence).
[Extends reviewer] Senior Backend Code Reviewer with 12+ years Java/Kotlin experience. Use when reviewing Java/Spring/Kotlin code, checking code quality and style, identifying code smells and anti-patterns, verifying security practices, ensuring test coverage, or running static analysis tools (Checkstyle, SpotBugs, SonarQube). Invoke alongside /rev for backend reviews.
Posts content to WeChat Official Account (微信公众号) via Chrome CDP automation. Supports article posting (文章) with full markdown formatting and image-text posting (图文) with multiple images. Use when user mentions "发布公众号", "post to wechat", "微信公众号", or "图文/文章".
Use a Bayesian intrinsic-growth valuation model to evaluate whether a company's market value sufficiently, excessively, or insufficiently prices its real 3-5 year growth. Use when the user asks for Bayesian valuation, intrinsic growth rate, implied growth, growth-hypothesis probabilities, FOMO versus fundamentals, or company analysis based on fundamentals, industry cycle, TAM, market share, margin, valuation multiples, and new information.
Use when the user asks to set, adjust, or optimize stop-loss and take-profit for BingX perpetual futures, including dynamic stop-loss, trailing take-profit, partial take-profit, ATR stop-loss, volatility stop-loss, break-even stop, and trailing stop. It calculates SL/TP based on ATR, volatility, and support/resistance through bingx-swap-market and bingx-swap-trade.
Author a Bounded backend: policy.json rules and invariants (rollingSum/windowSum/flowBound/conserve/tenantTag/tenantEdge/bound), functions (ctx.user/ctx.bounded/ctx.ai/ ctx.services/ctx.secrets), the actor and identity model (@user, runAs/actAs, @origin, service keys, reserved identity sets), data and queries, realtime/live rooms, and policy tests. Use when writing or changing server-side Bounded logic, policies, or the rules that govern who can do what. Part of the Bounded skill family; see the bounded skill to route across frontend, deploy, onchain, and teams.
Add onchain to a Bounded app: Solana collections, embedded non-custodial wallets for email/social users (@user.address, Turnkey by default), client- and server-signed transactions, DEX/perps trading patterns, and crypto payments (accept USDC/crypto non-custodially). Use for wallet, token, on-chain transaction, or crypto payment work. Part of the Bounded skill family; policy and the actor model live in bounded-backend.
Coach a client or team through defining a brand's visual identity from scratch — what it should make people feel, the muses it steals from, the distinct creative concepts, and the latitude it's allowed to flex within. Use before any creative direction, logo, or application work, or when the user mentions 'brand strategy,' 'what should our brand feel like,' 'brand workshop,' 'creative concepts,' 'brand personality,' 'find our visual direction,' or a brand that's undefined or being rethought. This is strategy, not execution.
Use this skill when the user asks to "intercept HTTP traffic", "modify web requests", "use Burp Suite for testing", "perform web vulnerability scanning", "test with Burp Repeater", "analyze HTTP history", or "configure proxy for web testing". It provides comprehensive guidance for using Burp Suite's core features for web application security testing.
Test an authorized web application for business-logic flaws and race conditions — the classes scanners cannot find. Model invariants (conservation of value, uniqueness, monotonicity, exclusivity), build an Actor x Action x Resource matrix, abuse state machines (skip/reorder/replay steps, limit-slicing), find numeric bugs (float-vs-decimal rounding, cross-currency refund arbitrage, negative amounts), stale feature gates, and saga gaps; prove concurrency bugs (double-spend, lost update, idempotency-key reuse) with controlled parallel requests. Use when the user mentions 'business logic testing,' 'race condition,' 'double spend,' 'TOCTOU,' 'concurrency bug,' 'idempotency,' 'coupon reuse,' 'workflow bypass,' 'limit bypass,' 'negative amount,' 'refund arbitrage,' 'parallel request attack,' or 'logic flaw'
Query cBioPortal for cancer genomics data including somatic mutations, copy number alterations, gene expression, and survival data across hundreds of cancer studies. Essential for cancer target validation, oncogene/tumor suppressor analysis, and patient-level genomic profiling.
Use when writing application code in Node.js / JavaScript / TypeScript — or any non-JVM language (Go, PHP, Ruby, Rust, C/C++) — that connects to a data source through a CData driver, after the connection and SQL have been validated with the cdata-cli discovery skill. Covers the CData ODBC Driver edition: confirming the system-installed driver, configuring a DSN or a DSN-less connection string, and connecting via the language's ODBC bindings (e.g. the Node `odbc` package). This is the cross-language build-phase companion to cdata-cli — the fallback for any environment that speaks ODBC.
Render a production-readiness GO/NO-GO grid for a database — runs a read-only audit, then maps the findings onto a fixed launch checklist (PITR/backups, RLS on tenant tables, FK indexes, money-as-numeric, timestamptz/UTC, connection pooling sized, migration reversibility, secrets-not-in-schema, charset/utf8mb4). Each row is PASS/WARN/FAIL/NEEDS-LIVE with the finding id, topped by a plain-language verdict. Read-only. Use when the user asks if a database is production-ready, ready to launch/ship, a go/no-go, a pre-launch or readiness checklist, or what to fix before going live.
Clean and normalize A-share financial data for modeling. Adapts the original clean-data-xls skill for Chinese financial statements, CAS conventions, and A-share data formats. Triggers on "A股数据清洗", "财务数据清洗", "clean financial data China", "数据清洗", or "normalize financial statements".
Track and report on A-share portfolio company performance for China-focused private equity funds. Monitors KPIs, financials, and strategic milestones. Adapted from the original portfolio-monitoring skill for Chinese portfolio companies. Triggers on "A股投后管理", "基金投后监控", "portfolio monitoring China", "monitor portfolio company", "投后报告", or "portfolio company review".
Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug development, clinical research, and evidence synthesis
Use when running the CloudCannon CLI — logging in, listing or creating sites, reading and writing files on a hosted site, triggering and inspecting builds, changing a site's build configuration, reading form submissions, or finding out which command and flags exist for a task
Use when calling the CloudCannon API from code — constructing a client, finding a site or organisation UUID, reading or writing files on a hosted site programmatically, triggering and inspecting builds, or reaching a CloudCannon endpoint the CLI has no command for (DAMs, backups, sync history, site scans, screenshots, provider connections, copying or deleting a site)
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.