Skills
99,448 packaged capabilities and playbooks for agents. Install any of them with one command.
All
Use when studying a SaaS web product from the outside in order to rebuild, clone or copy it (ClickUp, Pipedrive, Notion, a CRM, a project tool), when documenting its UX, screens, components, data model, business rules or API through a browser the agent drives, when assessing what would block a clone from launching (permissioned integrations, regulation, certifications), or when an agent must explore a live SaaS account without damaging production data or notifying real people.
Organizes and builds a per-session/class-meeting directory structure for courses or classes interactively and with full confirmation. Prepares subfolders for materials, presentations, exercises, games, practical work, and student assignment submissions.
Records the best scenes of a website or web app (WebGL hero, 3D, scroll) as 1080p MP4 for decks, uploads them to Figma Slides, and builds brand or product showreels in Remotion. Use on "record the site scenes", "site video for the deck", "showreel", "launch video", "gerar vídeo do site", "vídeo pro deck", "reel do produto", /site-reels.
Rules, Remotion helpers and audio scripts for stop-motion style video cut to music, proposing Remotion by default to make it. A low frame rate is kept on purpose, with one pose per eighth note of the song. Pages start on bar lines, clicks land on kicks and snares, and the skill teaches when to skip a beat. Use when making or reviewing stop-motion, low frame rate, beat-synced or music-synced video. Also use for cutting a video to a song, Remotion launch films cut to a track, compositions timed to a BPM, metronome or click tracks, kinetic type timed to a beat, or scenes played live on a web page in time with a metronome. It covers measuring a song's tempo, bars and drops, and deciding where a cut, a click, a hold or a transition should land.
Generates periodic learning progress report files and individual student learning portfolio books in Microsoft Word (.docx) or Excel (.xlsx) format, presenting work samples, grade history, and reflections on competency attainment.
Automatically assess student assignment files collected in the submissions folder against a grading rubric. Provide transparent analytical scores and constructive formative feedback, and automatically identify remedial and enrichment needs.
Use tdir-cli to query and directly generate the EMDR security operations threat daily report (including security incidents, endpoint and insight/ticket distribution, response times, and items requiring attention). Use when the user requests generating, recalculating, or reviewing an EMDR threat daily report or operations daily report. Does not handle TDIR global weekly reports, in-depth forensics of individual insights, or security incident response.
Verify web UI changes in headless Chrome with agent-browser, signed in as the project's Clerk test users, and run the project's relevant existing tests. Use after changing anything visible, or when asked to check, inspect, screenshot or exercise a browser flow.
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.
Create an evidence-backed DESIGN.md for any public website URL. Use when asked to extract a site's design system, colors, typography, spacing, radii, shadows, components, or to generate a design.md compatible with Google's design.md format. Composes the awwwards MCP inspection/capture tools; does not invent brand intent, source token names, or unobserved states.
Generates interactive quizzes and assignments based on educational board games (snakes and ladders, crossword puzzles, concept Monopoly, academic bingo, question mazes, spin wheels/Jeopardy) as standalone interactive HTML5 and printable worksheets (PDF/A4).
恢复被 C3RB3R / Cerber 系勒索软件（文件后缀 .L0CK3D、勒索信 read-me3.txt）加密的群晖（Synology DSM）或其他 Btrfs NAS 上的数据，无需密钥：利用 Btrfs 写时复制留下的旧 extent 逐字节还原原文件，并用 Btrfs 校验和逐块证实。覆盖 CoW / NoCOW 判定、子卷快照代数（lastsnap）效应、extent 树精确重组、大文件跨 extent 推测、统计、导出、验证和报告。只要用户提到 NAS / 群晖 / 黑群晖 被勒索、.L0CK3D、read-me3.txt、C3RB3R、Btrfs 文件被加密想恢复、"没有备份没有快照怎么救"，即使没提 Btrfs 或 extent，也应使用本 skill。Use for ransomware recovery of .L0CK3D files on Synology/Btrfs volumes without the key.
Assemble Chinese running-script calligraphy from original glyphs, look up character forms and sources, inspect radicals, and synthesize missing glyphs. Use for calligraphy composition, character images, or copybook references. Read this skill for exact CLI syntax before running commands
Connects player, item, upgrade, and enemy data through one stat model and a chosen defense formula (flat, ratio, level-scaled ratio, or capped percent), computes hits and seconds to kill and to die for each stage and enemy, and flags results outside designer target ranges. Use when setting or reviewing combat stats, choosing a defense formula, or checking difficulty per zone, level, or wave in any genre and engine.
Turn the changes in a git working tree into clean Conventional Commits: read the diff, run the repository's own check, stage by path, split unrelated changes into separate commits, write the message, and verify what landed. Use when: (1) the user wants to commit, save progress, record WIP or wrap up a finished task, (2) a working tree mixes unrelated changes that should become separate commits, (3) a change breaks existing usage and the release tooling must see it, (4) the user mentions: commit, commit this, commit my changes, save progress, WIP commit, conventional commit, commit message, git add, staged, untracked, BREAKING CHANGE, feat!, Co-Authored-By, pre-commit hook, "split this into commits". Carries the staging rules that keep secrets and build output out, the breaking-change markers that `bumpv` reads to choose a MAJOR release, the hook and amend rules, and a post-commit check that no attribution trailer landed. Any git repository and any stack; the repository's own check and documented conventions are the seam. Not a release tool, not a changelog writer and not a push or pull request flow
Models item enhancement (cost, success rate, and keep/downgrade/destroy on failure per level) and synthesis (fixed recipes and random merges that combine matching items into one of a matching set), computes the expected cost and attempts to reach each level, the value ratio of each recipe against stat budgets, and the expected crafts to get one specific result, and finds item-multiplication loops and items no drop, recipe, or declared source can produce. Use when designing or reviewing upgrade systems, crafting, merging, salvage, or item acquisition paths in any genre and engine.
Install the Datadog Agent on a Docker host—standalone Docker (Linux or Windows) or Docker Compose—with infrastructure metrics, container logs, APM trace intake, and DogStatsD enabled by default, plus optional live processes, tags, hostname, proxy, and container filtering. Keep the API key in a restricted env file rather than on the command line. Use when the user has Docker containers on a single server, wants to install Datadog on their Docker host, or wants to set up Datadog with Docker Compose. Does not install the Agent on Kubernetes or directly on a Linux, macOS, or Windows host (use dd-agent-install-kubernetes, dd-agent-install-linux, dd-agent-install-macos, or dd-agent-install-windows). Requires a Datadog account with a valid API key and application key; run `dd-account-setup` first if they are missing.
Install the Datadog Agent on Linux hosts—a single machine or a fleet—with support for cloud rollouts (AWS Systems Manager, GCP VM Manager, Azure Run Command), remote configuration management, proxy, FIPS, custom tags, and advanced configuration. Infrastructure metrics, logs, and the APM trace receiver are enabled by default; host Single Step Instrumentation is enabled only when requested (for an SSI-first request, use `dd-apm/linux-ssi` `agent-install`). Use when the user wants to monitor Linux servers, install the Datadog Agent on an Ubuntu or other Linux host, or roll the Agent out to an EC2 or other cloud VM fleet without SSH. Does not install the Agent on Windows, macOS, Docker, or Kubernetes (use dd-agent-install-windows, dd-agent-install-macos, dd-agent-install-docker, or dd-agent-install-kubernetes) and does not connect a cloud provider integration. Requires a Datadog account with a valid API key and application key; run `dd-account-setup` first if they are missing.
Set up Datadog Cloud Cost Management for AWS by configuring a Cost and Usage Report - either CUR 2.0 (recommended) or a Legacy CUR - and provisioning the S3 bucket, bucket policy, IAM read policy, role attachment, and Datadog registration with Terraform. Use when the user wants to track their AWS cloud costs, set up cost and usage reports, set up Cloud Cost Management (CCM) for AWS, set up CCM with CUR 2.0, or connect an AWS Data Export to Datadog. Does not connect a new AWS account to Datadog and does not set up cost management for other clouds. Requires an existing role-based Datadog AWS integration; run `dd-aws-integration` first if it is missing.
Set up AWS log forwarding to Datadog with Terraform: deploys the Datadog Forwarder Lambda in the user's AWS account, seeds the Datadog API key into a Secrets Manager secret out-of-band so it never lands in Terraform state, and registers the forwarder ARN on the existing AWS integration so Datadog automatically subscribes CloudWatch log groups and S3 buckets. Use when the user wants to forward AWS logs to Datadog, send CloudWatch logs to Datadog, or set up the Datadog Forwarder Lambda. Does not create the AWS integration itself or set up metrics collection. Requires the Datadog AWS integration (datadog_integration_aws_account); run `dd-aws-integration` first if it is missing.
Set up Datadog Cloud Cost Management for Azure with Terraform. Provisions (or reuses) a Storage Account and Container, creates actual-cost and amortized-cost Cost Management exports, grants the existing Datadog app registration read access through role assignments, and registers the exports with Datadog through datadog_azure_uc_config in a two-phase apply around the manual file-partitioning step. Use when the user wants to track Azure cloud costs, set up Azure cost exports for Datadog, or set up Cloud Cost Management for Azure. Does not create the Azure integration or its app registration/service principal. Requires an existing Datadog Azure integration; run `dd-azure-integration` first if it is missing.
Set up automated Azure log forwarding to Datadog by running Datadog's official Log Forwarding Orchestrator (LFO) install script through the Azure CLI - deploys the managed control plane that auto-discovers resources across the monitored subscriptions and provisions and scales the log forwarders itself, with no per-resource diagnostic settings. Use when the user wants to forward Azure logs to Datadog, send Azure resource logs to Datadog, or set up Azure log forwarding. Does not generate Terraform and does not create the Azure integration or set up metrics collection. Requires the Datadog Azure integration; run `dd-azure-integration` first if it is missing.
Set up the Datadog Confluent Cloud integration: create a Cloud resource management API key in Confluent Cloud (with the Confluent CLI or the console), register the account with Datadog, discover and register its Kafka clusters, connectors, ksqlDB and Schema Registry resources, and optionally add Schema Registry tags and Cloud Cost Management. Use when the user wants to monitor Confluent Cloud Kafka clusters, set up the Datadog Confluent Cloud integration, connect Confluent Cloud to Datadog, see Confluent metrics in Datadog, or monitor Kafka clusters on Confluent. Does not set up self-managed Kafka or the Datadog Agent. Requires a Datadog API key and application key; run `dd-account-setup` first if they are missing.
Set up Datadog Cloud Cost Management for Oracle Cloud Infrastructure (OCI) by enabling cost collection on an integrated parent tenancy—an API toggle on the existing tenancy integration, with no Terraform, storage buckets, exports, or extra IAM policies. Use when the user wants to track their OCI cloud costs or asks to set up Cloud Cost Management for OCI. Does not create the OCI tenancy integration itself or provision any infrastructure. Requires an existing Datadog OCI integration; run `dd-oci-integration` first if it is missing.
Scaffold a directions lab that shows shipped UI (Today) beside 2-3 design directions, with surface tabs, theme and animation toggles and the V1 MVP hover motion, registered in design-proposals Storybook. Use for a directions page or lab, or to explore design directions next to production.
Models currency income per stage (kills times enemy rewards, expected sell value of drops, other income) and an ordered purchase plan whose prices come from item prices, expected enhancement costs, crafting costs, permanent upgrade costs, or fixed amounts, then computes when each purchase becomes affordable within a run, which run a carried meta currency affords it, and how much currency is left over. Use when tuning rewards, prices, shop or upgrade pacing, or checking for currency piling up or running short, in any genre and engine.
Look up MCU peripheral registers, bit fields, reset values, and addresses (based on CMSIS SVD), with sources and evidence labels for every finding. Supports address reverse lookup; register value decoding and write-value calculation; bit-field quick reference and bitmaps; interrupt number and NVIC enable hints; CMSIS-style macro generation; cross-chip and peripheral-level comparisons; address range queries; SVD quality checks; local chip inventory and environment checks; Markdown table output; and parsed-result caching. Use when the user asks about a register, bit field, reset value, peripheral base address, or interrupt number; wants to decode or compute a register value to write, generate register macros, compare register definitions across devices, or find or verify SVD files on the machine. Keywords: 寄存器、位域、复位值、SVD、外设地址、寄存器值、掩码、位图、中断号、IRQn、NVIC、宏定义、对比、整体对比、质量检查、SVD 位置、芯片清单、读改写、USART1->CR1、register、bitfield、mask、reset value、decode、interrupt. Not for: pin multiplexing, manual chapter search, errata lookup, or verifying register writes in code (use embedded-register-verify).
Use when the user asks to fix, patch or upgrade a PHP vulnerability (e.g. 'Please fix my PHP vulnerability'), PHP2Shell, CVE-2026-109618 or CVE-2026-109619, or to find vulnerable PHP versions in Dockerfiles, distro packages, source builds, setup-php CI, Helm/IaC or Ansible/Chef/Puppet. Read-only inventory, approval gate, regression tests, focused PRs.
Align the current project's PRODUCT.md, DESIGN.md, GLOSSARY.md, and ARCHITECTURE.md after meaningful changes, and write the project Flow block on request. Use when the user says "update the docs", "sync the context", "keep the docs aligned", or "set up Flow here".
Futu `futu` CLI market-data skill. Use for stock, option, and futures quotes, K-lines, snapshots, tickers, intraday data, order books, rankings, capital flow, company profiles, financials, shareholders, valuation, plates, IPOs, calendars, watchlists, and paginated queries. Do not use it to place orders
Set up a headless Mac (Apple silicon), Linux or Windows machine over SSH, step by step, from "an admin account with a password and SSH on" to a configured machine with key-only SSH, automatic sign-in, never-sleep settings and optional Tailscale - on a Mac with Determinate Nix and nix-darwin, on Linux with a NixOS module (installing NixOS with nixos-anywhere if the user wants) or a distro-neutral script for Debian, Ubuntu and Fedora, on Windows 11 or Windows Server with a rerunnable PowerShell configuration - then restart it and confirm it comes back. Use when the user wants to set up, configure, update or check a headless Mac mini, Linux server, Windows PC or other machine they reach only over SSH. The admin password stays in the user's secret store (Automic Vault, 1Password, Bitwarden, any command, or a private env file); you only ever name the store entry.
Build from a written issue or task, collaborating with the user: read the issue and related open work, ground it in the code, clarify requirements and design with the user, then implement after they confirm the plan. Use when the user says let's build, build together, or asks to build from an issue or task description.
Use the public `orca` CLI to operate Orca-managed worktrees, folder contexts, terminals, repos, automations, artifacts, worktree comments, and the browser embedded inside the Orca app. Use when the user says "$orca-cli", "use orca cli", "Orca worktree", "child worktree", "cardStatus", "spawn codex/claude in a worktree", "read/wait/send Orca terminal", "terminal send", "full handoff", "handover", "give this to another agent", "another worktree", "Orca browser", "orca artifacts", "share HTML/Markdown", "public artifact link", or "control the browser inside Orca". Prefer this over raw `git worktree`, ad hoc PTYs, Playwright, or Computer Use when the task touches Orca-managed state. Use Computer Use for browser windows, webviews, or desktop UI outside Orca's embedded browser.
Rebuild a web page, section, component or interaction from a reference (a live URL, a local HTML file, a screenshot or design export, or a screen recording or GIF) inside the user's own codebase. Then measure the rebuild against the reference (element boxes, computed styles, pixels, motion timing and easing) and iterate until a numeric Replica Score passes. Use when the user wants to clone, replicate, recreate, copy, port or match a site, landing page, hero, navbar, pricing table, card, modal, footer, hover effect, scroll reveal, page-load animation or any other UI, or to "make it look/feel/move like" one. Also use when they say "pixel-perfect", "1:1", "exactly like this" or "same as <url>", or hand over a screenshot, Figma export or video and ask to build it, including when they want their own copy, brand or extra features on top.
Reviews a git diff through reviewer subagents on each lens (big picture, detail), then checks and triages the findings and fixes clear problems. Use when the user asks for a code review, PR review, sanity check on changes, or reviews with specific or multiple models.
Find where an agent pipeline can swap frontier models for cheaper ones without losing quality. Drive the installed rightmodeler TypeScript CLI through its resumable pipeline, interpret its machine protocol, present per-family verdicts, and open a reviewed model-swap pull request when the evidence supports one. Use when the user wants to cut model spend, right-size models per task, benchmark cheaper model substitutions, or analyze an agentic pipeline for cost optimization.
Initialize a new project from flow-next or flow-mono with verified setup, renamed identity, and an independent initial Git commit, while explore shapes the product. Use when the user says "start a Next.js project", "start a new project", or "start a monorepo".
Sets stat budget curves per tier, zone, or level with per-stat costs and multipliers (rank, rarity, slot), checks every item and enemy against its expected budget, drafts new items and enemies from archetypes that split the budget across stats, and suggests stat costs from the combat formula. Use when designing tier or zone progression, adding items or enemies so they fit a curve, finding over- or under-budget entries, or deciding how much one stat point is worth, in any genre and engine.
Sync a repository's documentation with what its code actually says: versions, dependencies, commands, project structure and feature claims in README.md, CLAUDE.md, AGENTS.md and docs/, each verified against the manifest, lockfile, scripts and files before it is written, with human prose, tone and section order left as they are. Use when: (1) a dependency, framework or runtime version changed and the docs still name the old one, (2) scripts, Makefile targets or the directory layout changed, (3) a feature was added, renamed or removed and the docs may no longer match, (4) an agent instruction file tells agents to run a command that may not exist, (5) the user mentions: sync docs, update the README, docs are stale, docs out of date, outdated version in README, fix CLAUDE.md, AGENTS.md, package.json, lockfile, pyproject.toml, Cargo.toml, go.mod, "npm run lint" missing script, "docs: sync documentation with codebase state". Carries the ground-truth table per ecosystem, the rule for declared range against resolved version, the flag-don't-guess rule for unverifiable feature claims, and a three-part report of changed, verified and flagged. Works on any project type, Node, Rust, Python, Go or a repository with no manifest at all; the repository's own manifests and files are the seam. Not a changelog or version bump tool, not a doc writer for missing files, and not an audit of the code against the docs
Wire Redis Agent Memory into an existing agent with redis-iris so it remembers users across sessions. Asks five questions (what to remember, what to share, what never to keep, how long to keep it, whether users can be forgotten), writes the answers to service.yaml, provisions the service from the terminal with `iris agent-memory service create`, then wires recall and write-back into the agent's turn in any framework. Use when the agent forgets users, uses InMemoryStore or a checkpointer only, keeps memory in a dict or local DB, or the user asks for long-term memory, recall, or right-to-erasure.
Add Redis Iris Agent Playbooks to an existing agent. Use when approved answers or repeatable procedures live in prompts, document retrieval, or a semantic response cache. Connect or provision a Playbook, publish FAQs and Skills, and verify the first application turn with optional review proposals.
Put the MCP servers an existing agent uses behind one Redis Iris Context Gateway with redis-iris, so the agent connects to one MCP endpoint with one agent key instead of configuring each server and its secret. Asks whether the Gateway is in Redis Cloud or self-managed, then five questions (which MCP servers and secrets the agent has today, how many tools it sees, which read-only tools may be cached, which tools return large results, whether the framework speaks MCP itself). Self-managed, it provisions the Gateway and its Upstreams from the terminal with `iris context-gateway` and sets cache and compression policies. In Redis Cloud the developer creates them in the console. Then it points the agent at the Gateway in any framework and verifies it with `tools list` and `tools call`. Use when the agent configures several MCP servers one by one, carries one secret per server, loads too many tool schemas into the prompt, or the user asks for Context Gateway, one MCP endpoint, tool caching, or result handles.
Replace an existing agent's hand-written routing (keyword if/else chains, regex, or an LLM call that only picks a route) with a Redis Iris Intent Router through redis-iris, so a message maps to a defined intent and its dispatch target by example phrasings and a score threshold. Asks five questions (what the routes are today, a few real phrasings per route, what each route dispatches to, what happens when nothing matches, which embedding model), writes the answers to intents.yaml, provisions the Router from the terminal with `iris intent-router service create`, loads the intents with `iris intent-router intents add`, then wires `router.match()` where the agent decides today. Use when the agent routes with keywords or an extra LLM call, or the user asks for intent detection, intent routing, or semantic routing.
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.