Skills
100,696 packaged capabilities and playbooks for agents. Install any of them with one command.
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Guide for convex-helpers library patterns including Triggers, Row-Level Security (RLS), Relationship helpers, Custom Functions, Rate Limiting, and Workpool. Use when implementing automatic side effects, access control, relationship traversal, auth wrappers, or concurrency management. Activates for triggers setup, RLS implementation, custom function wrappers, or convex-helpers integration tasks.
Create Architecture Decision Records (ADRs) to document significant technical decisions, their context, alternatives considered, and consequences. Use when making architectural choices, selecting libraries/frameworks, or designing system components.
Use when an agent needs to author or reply to crit inline comments programmatically (including multi-agent workflows commenting on shared code/plans/docs/proposals), publish or unpublish a crit review with crit share, sync a crit review to or from a GitHub PR or GitLab MR, or read/interpret a crit review JSON file. Covers crit comment, crit share, crit unpublish, crit pull, crit push, review file format, and resolution workflow. Not for invoking an interactive review loop — that's the `/crit` command.
Scrape a single known URL into clean markdown / HTML / links / structured JSON with fastCRW. Use when you already have the URL and want the page content — "scrape", "grab", "fetch", "pull", "read this page", "get the content of". Handles JavaScript-rendered SPAs automatically. Step 2 of the crw workflow ladder.
Manage the public daemon profile — a digital representation of what you're working on. DaemonAggregator reads LifeOS sources (TELOS, KNOWLEDGE, PROJECTS, MEMORY/WORK, identity) → daemon-data.json. SecurityFilter strips names/paths/credentials via deterministic patterns (NOT LLM). Workflows: UpdateDaemon, ReadDaemon, PreviewDaemon, DeployDaemon. USE WHEN daemon, update daemon, daemon profile, deploy daemon, preview daemon, read daemon, public profile, digital presence. NOT FOR LifeOS system management.
Generates Dart models from a JSON structure using json_annotation and equatable. Use this skill when the user provides a JSON object and wants the corresponding Dart model classes generated, or asks things like "generate a Dart model for this JSON", "create a model from this response", "dart model from json". Always use this skill when the user provides JSON and needs Dart model output.
The 都爆鸭 platform's **invocation gateway** (infrastructure Skill, **does not handle business intent**): how to carry authentication, how to choose between the two non-fallback routes, how to decode the unified envelope and error codes, and one rule — **pull the input spec right before invoking**. Not responsible for writing articles / finding topics / making covers / checking prohibited words — those go through `dby`. Trigger words: doubaoya invocation protocol / invocation gateway / DOUBAOYA_API_KEY / operationKey / execution.target / inputContract / input spec / unified envelope / SKILL_NOT_FOUND / ENDPOINT_NOT_FOUND / DEDICATED_ROUTE / NO_RESULT / CAPABILITY_UNAVAILABLE / which route to hit; and when calling 都爆鸭 APIs: "401 / 404 / 429 error", "can't connect", "how to authenticate", "requestId".
Entry point for Datadog onboarding. Takes a developer's plain-language goal, ensures a valid Datadog account with dd-account-setup, asks dd-product-recommender which products fit, detects the project's platform and cloud, then composes an ordered plan across the existing skills (agent install, product enable, verify, and optional cloud integration) and dispatches to each by source URL — honestly flagging products with no skill yet. Use when the user says "set up Datadog", "onboard my app / this repo to Datadog", "instrument my project", or states a monitoring goal without naming a specific product or skill.
Alias for `/origin:handoff` — symmetric brief/debrief naming. Same behavior: end-of-session ritual that writes session log + project status + granular MCP captures. Invoked as `/debrief`. Use when the user prefers the brief/debrief pair over brief/handoff.
Load PROACTIVELY when task involves investigating errors, diagnosing failures, or tracing unexpected behavior. Use when user says "debug this", "fix this error", "why is this failing", "trace this issue", or "it's not working". Covers error message and stack trace analysis, runtime debugging, network request inspection, state debugging, performance profiling, type error diagnosis, build failure resolution, and root cause analysis with memory-informed pattern matching against past failures.
Use when writing or reviewing JavaScript/TypeScript in this repo that calls Deepgram Text-to-Speech v1 (`/v1/speak`) for audio synthesis. Covers one-shot REST via `client.speak.v1.audio.generate` and streaming WebSocket via `client.speak.v1.createConnection()` / `connect()`. Use `deepgram-js-voice-agent` when you need full-duplex STT + LLM + TTS instead of one-way synthesis. Triggers include "TTS", "text to speech", "speak", "aura", "streaming TTS", and "speak.v1".
Interview the user to define or revise the app's overall product direction, then preserve the confirmed meaning in root PRODUCT.md. Always use for a new app direction or any app-wide change to users, usage situations, problem, promised change, core loop, durable boundaries, experience principles, success signals, assumptions, or unknowns, even when PRODUCT.md is not named. Start from an existing definition or a rough app direction. Do not use for blank-page idea discovery, architecture, or shaping or specifying one feature or work unit.
Advanced 7-step hierarchical design prompt generator for AI web development tools (Lovable, Cursor, Bolt). Generates domain-aware, user-journey-based design prompts with emotional design considerations. Triggers on "디자인 프롬프트", "웹 디자인", "Lovable 프롬프트", "랜딩페이지 만들어줘", or any AI web builder prompt requests.
Provides comprehensive guidance for Detox mobile testing framework including React Native testing, E2E testing, and test synchronization. Use when the user asks about Detox, needs to test React Native applications, write E2E tests for mobile apps, or configure Detox.
Use when Codex is building or iterating on a web game (HTML/JS) and needs a reliable development + testing loop: implement small changes, run a Playwright-based test script with short input bursts and intentional pauses, inspect screenshots/text, and review console errors with render_game_to_text.
Recover the original logic from code protected by a virtualization obfuscator — VMProtect, Themida/WinLicense, Code Virtualizer, or a custom opcode VM — by locating the VM dispatcher, reverse-engineering the handlers into semantics, extracting the virtual bytecode, and lifting it to a simplified IR with Triton, miasm, or VTIL-based tools. Use when a function became a giant fetch-decode-dispatch loop, when analysis shows a handler table instead of normal code, or after unpacking reveals a virtualized core.
Use this skill whenever the user is writing, debugging, or building Python algo trading code using the Dhan-Tradehull library (pip install Dhan-Tradehull). Triggers on: any mention of Tradehull, Dhan_Tradehull, tsl., get_ltp_data, order_placement, ATM_Strike_Selection, get_option_chain, get_historical_data, super order, forever order, conditional trigger, OI scalping, options strategy using Dhan, place order Dhan Python, Tradehull authentication, get_positions, get_holdings, enable_pnl_based_exit, get_option_greek, margin_calculator, or any TradeHull course code task. Always use this skill before writing any Tradehull code — even for simple snippets — to ensure correct method signatures and patterns.
Establish the mechanism behind a hard, intermittent, recurring, or performance failure from a faithful reproduction or distinguishing runtime evidence. Use when the user asks to diagnose or debug, or when an authorized repair remains causally uncertain after direct inspection; do not use for simple factual questions, obvious local failures, proactive audits, or routine test fixes.
Runs the react-doctor scanner on a React package, fixes its error diagnostics, and re-runs until none remain. Use when the user says "health-check the React code", or when React components or hooks changed, when finishing a React feature or bug fix, or when asked to health-check React code.
Use when the user asks to test, check, QA, or audit a website before a launch, after a migration, as a periodic review, or for due diligence, including just one area (technical, performance, accessibility, SEO, GEO and AI search, e-commerce, email, privacy and legal, security, analytics, content, monitoring, or client handoff).
Use whenever writing, modifying, reviewing, or creating code in a Dido Nuxt frontend, even for a small component or style tweak (pages, Vue components, composables, Pinia stores, SCSS with slamp and react, i18n, Nuxt configuration, GraphQL queries, third parties, animations, accessibility, and SEO), and when starting a new site from the Nuxt boilerplate.
Build a digital twin of yourself, meaning photoreal stills of you in your own real room, talking video clips of you, and lines in your own cloned voice, that people who know you accept as you. It's a proven workflow (160+ numbered stills over two dozen rounds, 20+ talking drafts and a voice taken from 8.7 to 9.2/10 on one creator's twin, Nov 2026). It covers consent, picking references from your own recordings, writing an identity prompt, the 4-part prompt stack on Seedream 5 Pro, your-real-room-only with the camera as the only variable, 3 images at a time, cinematic looks taken from reference videos as words, measuring face proportions, the audit and paste-back fix, an instant voice clone with an audio tag, a speaker-similarity scorer, Seedance 2.5 draft talking clips, and the traps (voice verification lockouts, iMacs, grey hair, wide mouths, other people's faces bleeding in). Use it whenever someone wants AI images, video or voice of THEMSELVES, even if they only say "my digital twin", "AI headshots of me", "a video of me talking", "clone my voice", "make me a presenter clip", "an AI avatar of me", "me at my desk", "a talking-head intro without filming" or "creator or founder content with my face". Only for your own face and voice, or someone who gave documented consent.
Compute Rayleigh and Love wave phase/group dispersion and sensitivity kernels for one-dimensional isotropic layered Earth models. Use when forward modelling velocity profiles, comparing layered models, or preparing numerical derivatives for a separately defined inversion. Does not extract observed dispersion from waveforms or perform tomography.
Guide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar documentation tasks.
Run a full review of an Elastic documentation PR against the docs team review checklist — user focus, technical accuracy, applicability, maintainability, language, and style. Runs the companion review skills and merges everything into one report with a recommended approve, comment, or request-changes call. Use when reviewing a docs PR, checking a branch before requesting review, or deciding whether a docs change is ready to merge.
Generate a Dynatrace Gen 3 **KPI dashboard** (15–20 business KPIs, required map tile, branded section dividers) and a matching 30‑minute BizEvents injector for a named company, then deploy both via `dtctl`. Use this skill ONLY when the user explicitly asks for a Dynatrace KPI dashboard, business-event KPI demo, BizEvents injector, or a "KPI dashboard for <company>" — do NOT use for generic Dynatrace dashboards (SRE, infra, k8s, services, RUM) or for editing existing non-KPI dashboards. Triggers include phrases like "generate a KPI dashboard", "build a BizEvents demo for <company>", "spin up a KPI dashboard + injector", "/generate-kpi-dashboard". Requires `dtctl` authenticated to a Dynatrace Gen 3 tenant.
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.