Skills
96,770 packaged capabilities and playbooks for agents. Install any of them with one command.
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Operate Orca-managed worktrees, folder contexts, terminals, repos, automations, artifacts, skill sharing, worktree comments, and Orca's embedded browser through the `orca` CLI. Use when the user says "$orca-cli", "Orca worktree", "child worktree", "spawn codex/claude in a worktree", "read/wait/send Orca terminal", "handoff" / "handover" / "give this to another agent", "Orca browser", "orca artifacts", or "share skills". Prefer it over raw git worktree, ad hoc PTYs, or Computer Use when Orca state is involved. Use Computer Use only when a visible window needs GUI control that a CLI, filesystem, or API cannot do.
Transform mocked-up UI specs (specs-ui skill project) into a purely UI clickable prototype in HTML + Tailwind + Alpine.js: main flows are wired up (navigation, forms, states, simulated data stored in the browser, reset), with guided test scenarios for user testing and demos, published as a multi-page artifact. Use whenever someone wants a prototype, clickable mockup, interactive demo, user-testable flow, user test, or a version "you can click through" based on existing specs or mockups, even without saying "prototype".
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.
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.
Create an AI talking head from the user's own photos plus a voice sample, or from a self-recorded video by extracting face frames and speech. Use an authorized cloned or existing ElevenLabs voice and a new script to generate speaking shots with fal MiniMax H3, narration and editable motion graphics, then render an MP4. Use for AI avatars, presenter videos, personal explainers and scripted on-camera clips. For a recording that only needs graphics without generating new speech, use a recording-editing workflow instead.
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.
Edit and compose video on a timeline. Use when the user wants to add background music, a voiceover or another audio track, put text, a logo or an image overlay on a video, join several videos or images into one with fades or other transitions, add animated or word-by-word karaoke captions, change the resolution or aspect ratio of a composition, or generate music, voiceover, images or video with AI for a composition. Static subtitles with a chosen font and position belong to video-subtitles.
Find a moment in a video or ask a question about it. Use when the user wants to search inside a video, a library, or a meeting recording (“find where they talk about pricing,” “which scenes show a phone,” “what did she say about hiring”), get an answer with timestamps, count what appears, or get a clip of that moment. A highlight reel from a prompt, a cut by time range, or a vertical cut is video-clips. Works on YouTube links, public URLs and the user's VideoDB videos.
Subtitles, captions and transcripts for a video or audio file. Use when the user wants a transcript (plain or timestamped) of a video, podcast or call recording, static subtitles burned in with a chosen font, colour and position, a transcript or subtitles translated into another language, or dubbing. Animated or karaoke captions belong to video-edit. Works on YouTube links, public video URLs, audio files and media already in the user's VideoDB account.
Expert data extraction guide. Starts with a structured intake to understand the target. Always tries the cheapest path first (HTTP requests → browser fingerprinting → headless browser). Covers TLS/HTTP fingerprint impersonation (curl_cffi, primp, rnet), the modern stealth-browser stack (patchright, camoufox, nodriver), the anti-bot vendor matrix (Cloudflare, DataDome, Kasada, Akamai) with per-vendor bypass, CAPTCHA/Turnstile solving, proxy networks and managed unblockers (Zyte API, Web Unlocker) with geo-targeting, structured-data extraction (JSON-LD/microdata/OpenGraph), AI/LLM-driven and adaptive extraction (scrapling, crawl4ai, firecrawl), site-stack playbooks (Next.js App Router/RSC, Tableau, OData, PX-Web, SDMX, ASP.NET, GraphQL, SPAs), browser request injection, live request interception, and clean OOP architecture standards for scrapers and extracted data. Use whenever the user wants to scrape/extract data from a website or API
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).
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
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.
Use when a human wants to create, hire, activate, or set up a new AI employee from a plain-English description, e.g. wanting something that writes a weekly recap or replies to guest messages. Drives the Hiring Dozal's multi-turn setup wizard (the hiring chat), relays its button questions (show me first or just send it) to the human, and hires the finished Dozal. Use it for any new-employee request. Load operate-ai-employees first for auth and base-URL setup.
Investigate a LangSmith experiment with the LangSmith CLI, identify examples with poor evaluator results, explain likely causes using run evidence, and propose targeted fixes. Use when a user asks why an experiment performed badly or which evaluated examples need attention.
Use when a human wants to see, list, pause, reactivate, rename or inspect their existing AI employees (config, status active/paused/draft), or manage connected apps, schedules, handoffs, members and invitations, usage and bills, e.g. what employees do I have, pause the recap bot, how did last Friday go. Not for running one now (run-ai-employee), a task's output, approval or logs (monitor-and-review-ai-employee-work), or creating one (hire-ai-employee). Load operate-ai-employees first.
Use when a human asks whether an AI employee task is done, wants to see its output, or wants to approve or reject its work: is the recap ready, show me what it wrote, approve it, reject and shorten it, why did that run go wrong, show its logs, watch it live. Reads task status via phase_category, drives the approve/reject decision, and reads run logs, activity and live status. Load operate-ai-employees first for auth setup.
Use when a human asks you to operate their AI Employee platform account: hiring an employee, running one, checking on a task, approving or rejecting work, listing or pausing employees, or managing connections, schedules, handoffs, members, usage, bills, activity and run logs. Load this first to route between the four job skills. The umbrella skill: dze_ API key auth and its level, the production base URL, tenant resolution, the async model, and person-only steps.
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.
Reviews PostHog's warehouse suggestions with a person and acts on them. Explains why a view should be materialized, unmaterialized, certified or deprecated using the numbers in the suggestion, changes a materialize suggestion's refresh mode, keys or interval when the person wants something else, then accepts or dismisses it. Use when the user asks what PostHog suggests for their data warehouse, whether to materialize a view, why a view should refresh incrementally or every few hours, or wants to accept, change or dismiss a warehouse suggestion.
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.
Use when a human wants to run, trigger, start, or test-run an existing AI employee, e.g. run the recap bot now, kick off the guest responder, or run it once per topic from a list of inputs. Triggers the employee, can dry-run to list required inputs, and hands back task handles without blocking. Load operate-ai-employees first for auth; use monitor-and-review-ai-employee-work to check the result.
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
Remove the “AI look” from websites, landing pages, apps, dashboards, docs, and slides (HTML/CSS, Tailwind, React, shadcn). Use when creating or reviewing any interface, or when someone asks for design that feels “less AI,” “more human,” “less templated,” or “less SaaS,” or asks for visual references (Pinterest, Dribbble, Awwwards). Covers the entire process: brief, pre-code sketch, browser-based reference search, design system, build, and detector audit. Catches the tells people recognize in 2 seconds: an eyebrow above the title, a gradient or differently colored word in the title, a card with a side border, a chip with a pulsing dot, emoji in place of an icon, Tailwind purple, pills everywhere, glassmorphism, “how it works” in 3 steps, Playfair with italics at the end, a site without images, a SaaS look for a bakery. Based on the 51 replies to @greco_dev’s thread (Oct 2026).
Bans the 43 tells of a vibecoded website (purple gradient on black, indigo Tailwind buttons, bento grid, liquid glass, sparkles icon, fake counters, "Most popular" pricing, the "Create Next App" tab, no legal pages...) while Claude builds or reviews a site, so it looks made by a human. Use when building, redesigning or reviewing a website, landing page or web app UI, or when the user types /anti-vibecode, "vibecodé", "ça fait IA", "looks AI generated".
Produz aulas guiadas em HTML sobre qualquer assunto — telas curtas com pouco texto, um botão Continuar, mocks realistas da ferramenta ou situação, diagramas animados e prática com feedback — e as revisa quadro a quadro via Playwright. Use quando o usuário quiser aprender nesse formato ou transformar material em uma aula interativa. Pergunta apenas idioma, assunto e profundidade ou quantidade de telas; executa pesquisa, roteiro, design, motion, captura, correção e entrega com os recursos incluídos.
Make videos in pure code (mp4, 16:9 and 9:16): narrated explainers with captions and music, and promo / launch videos for websites, apps and software with beat-synced music and sound effects. The user picks only the style: whiteboard, risograph, ink-wash (水墨), launch motion, origami, pop art, op art, Matisse cut-outs, ASCII art, shadow puppets (皮影戏), Bauhaus, pixel art, chat log, toy 3D, old newsreel, film-room breakdown, suspense mystery, isometric miniature world, movie trailer, news clippings, manga (日漫), animated map. Use for science / concept explainers, problem walkthroughs, vocabulary, history, places and maps, how-tos, news / data, and product promos from a URL. Use when the user asks for an "explainer video", "whiteboard animation", "a promo / launch video for this website / app", or in Chinese "做个科普视频" "把这道题做成讲解视频" "白板动画" "讲个历史故事的视频" "给这个网站 / App 做个宣传片" "产品发布视频", or names one of the styles (孔版印刷, 水墨, 折纸, 波普, 欧普, 剪纸, 字符画, 皮影戏, 包豪斯, 像素, 聊天记录, 玩具三维, 老新闻片, 录像分析, 悬疑探秘, 等距微缩世界, 电影预告片, 剪报解说, 日漫, 地图动画).
Design, improve, and validate UI/UX for applications, websites, native interfaces, and games: an art direction derived from the product, a coherent visual system kept in the project's DESIGN.md (read first, created when missing, the single source of interface values), measured layout geometry (equal spacing, shared alignment lines, content centered inside small controls, nothing clipped or touching its container edge), a catalog of AI-slop patterns that rejects page narration and redundant helper text, a living motion language (press feedback, transitions, choreography, reduced motion), an Apple-like ultra-minimal default style, an opt-in pool of signature effects, clear actions, accessibility, drag and drop anticipated from the start (drop zones for every upload), and real states (including skeleton loaders and loading splash) without AI slop. Use for interface creation, redesigns, focused UI changes, animation and interaction polish, design plans, and UX audits; not for backend-only tasks.
100 questions about Binance Agentic Wallet. Uses Chinese Q&A to guide an agent in understanding Binance on-chain wallets, choosing official baw routes, checking transaction approvals and risk boundaries, and designing constrained automation extensions. Covers meme coin risks and honeypot detection, rug pull prevention, and verifying smart-money signals. For product questions, troubleshooting, trading strategy constraints, meme coin risk control, and wallet workflows; does not replace the official wallet skill and is not for placing Binance exchange futures orders.
Runs a local (LAN) and instant public host (Zero-Config Tunneling via Cloudflare/Localtunnel) for simultaneous multiplayer educational quizzes and board games in a classroom, without router configuration or a paid domain. Includes an automatic gradebook (real-time grade ledger), instant QR Codes for student smartphones, and export of grade summaries to Excel/JSON.
Avoid designs that inflate bills on Cloudflare (Workers, static assets, KV, D1, R2, Durable Objects, Queues, Workers Logs), and choose a cost-effective approach. Use when designing what to deploy on Cloudflare, adding a Worker or binding, deciding how to serve pages or data, or writing loops or retries.
Assess, set up, and verify how an AI development environment uses an organization's actual design system. Use when someone wants to keep AI on their system's rails, connect system knowledge and tools to coding agents, establish reuse and gap policies, or check whether those guardrails work. Focuses on the workflow and its evidence; ordinary page building or a full system inspection alone does not require this skill.
Write the observable contract for a User Story so the TESTER and DEV can work in parallel without seeing each other: assemble the context package (HU + story ADRs + Tech Design section), define inputs, per-case outputs, errors, and non-negotiable names with the source of each line, list decisions the HU left open, and stop for human approval. Use when the LEAD takes a user story to build, or when asked to write, draft, or version the contract/spec of a user story
Researches evidence unavailable locally: external documentation, public repositories at specific refs, archives, and published dependency artifacts (JARs, source JARs, POMs, dependency graphs), reusing a persistent cache of Git clones and Maven artifacts. Use for library docs, upstream source and history, dependency source or metadata, or any question needing external evidence
Use when the user asks to fix, patch or upgrade a self-managed GitLab vulnerability (e.g. 'Please fix my GitLab vulnerability'), CVE-2026-110264 or the GitLab 19.5.1 critical patch release, across Omnibus, Docker, Helm chart and IaC deployments. Read-only inventory, approval gate, post-deploy checklist, focused PRs.
Humanize prose or draft it from supplied facts when explicitly asked to "humanize", "de-AI", "remove AI-sounding language", or write in a human voice. Simplify by cutting filler, stale content, and needless complexity. Confirm scope each run and offer four voice presets.
Build NHCX (India's National Health Claims Exchange) payer communication into an existing HMIS: receiving payer queries, notifications and notes on a pre-authorisation or claim, replying with text and documents, and acknowledging notifications, with the embedded NHCX gateway it needs. Use when a hospital system must answer insurer or PMJAY queries over NHCX.
Build NHCX (India's National Health Claims Exchange) payment notices into an existing HMIS: receiving the payer's payment notice and reconciliation breakdown, matching it to the claim, and acknowledging it, with the embedded NHCX gateway it needs. Use when a hospital system must record insurer or PMJAY payments arriving over NHCX.
Build NHCX (India's National Health Claims Exchange) claim reprocess and balance release into an existing HMIS: asking the payer to look again at a decided claim, asking for the unpaid balance of a partly paid claim, and applying the payer's answers, with the embedded NHCX gateway it needs. Use when a hospital system must contest a claim decision or recover a withheld balance over NHCX.
Operate Orca-managed worktrees, folder contexts, terminals, repos, automations, artifacts, skill sharing, worktree comments, and Orca's embedded browser through the `orca` CLI. Use when the user says "$orca-cli", "Orca worktree", "child worktree", "spawn codex/claude in a worktree", "read/wait/send Orca terminal", "handoff" / "handover" / "give this to another agent", "Orca browser", "orca artifacts", or "share skills". Prefer it over raw git worktree, ad hoc PTYs, or Computer Use when Orca state is involved. Use Computer Use only when a visible window needs GUI control that a CLI, filesystem, or API cannot do.
Audit the skill inventory for quality, coverage, and staleness. Detect overlapping, incomplete, or outdated skills and produce a health report. Activate when: skill audit, stocktake, skill inventory, check skills, which skills exist, audit skills, skill quality, skill coverage.
Help a person with no prior knowledge decide whether their website needs a content management system (CMS), and set it up if needed, for example Strapi in Docker on the Albatros server, accessible through a secure tunnel. Explain CMS using the image of a bulletin board. Use this skill for “CMS,” “Strapi,” “change content myself without code,” “blog,” “news,” “manage events,” “my colleague should be able to edit text,” “WordPress,” and “admin area.”
Work step by step with a person who has no prior knowledge and their AI to improve a small website's usability and appearance. First review it from three perspectives (flows, access, states, and language), then fix usability, offer three clearly different directions to choose from, set fixed values for colors, typography, and spacing (tokens), and rebuild all pages with photos at mobile and desktop widths. Use this skill for “design,” “looks boring,” “looks homemade,” “make it prettier,” “colors,” “font,” “redesign,” “three options,” “looks unprofessional,” and “layout.”
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.