Skills
99,064 packaged capabilities and playbooks for agents. Install any of them with one command.
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Optimize Next.js App Router data fetching by converting slow client-side fetching to fast server-side fetching using React Server Components (RSC). Use when: - User reports slow initial page load with loading spinners - Page uses useEffect + useState for data fetching - StoreContext/useStore pattern causes waterfall fetching - Need to improve SEO (content not in initial HTML) - Converting "use client" pages to Server Components Triggers: "slow loading", "optimize fetching", "SSR data", "RSC optimization", "remove loading spinner", "server-side fetch", "convert to server component", "data fetch lambat", "loading lama"
Use when designing, building, reviewing, or fixing any right-to-left (RTL) user interface—Persian/Farsi (فارسی), Arabic, Hebrew, Urdu—on the web (React, Next.js, Vue, Tailwind, plain CSS) or Flutter, even if the user only says the app is Persian/Iranian without mentioning RTL. Covers layout direction and mirroring, which icons flip and which never do, bidirectional (bidi) text with LTR islands (URLs, emails, phone numbers, code), Persian vs Arabic-Indic vs Latin digits, Jalali (Shamsi) dates, Persian typography (font pairing, line height, the letter-spacing trap, ZWNJ نیمفاصله), font licensing, logical CSS properties, form input direction, and long-text overflow. Also use when Persian/Arabic text renders incorrectly or looks “off,” when localizing an LTR app to RTL, or to audit existing code for RTL violations with the bundled zero-dependency detector. Not for backend-only or non-UI tasks.
Rust performance optimization covering memory allocation, ownership efficiency, data structure selection, iterator patterns, async concurrency, algorithm complexity, compile-time optimization, and micro-optimizations. Use when optimizing Rust code performance, profiling hot paths, reducing allocations, or choosing optimal data structures. Complements the rust-refactor skill (idiomatic patterns and architecture). Does NOT cover code style, naming conventions, or project organization (see rust-refactor skill).
CRM data quality, deduplication, enrichment automation, record matching, and data decay management. Use when CRM is full of duplicates, records are outdated or decaying, fields are missing or inconsistent, job titles and industries don't match across records, you're not sure how bad your data quality is, or enrichment keeps overwriting good data. Do NOT use for one-time enrichment of a prospect list (use /sales-enrich), building new prospect lists (use /sales-prospect-list), or ZoomInfo-specific config (use /sales-zoominfo). For platform-specific help, use /sales-zoominfo.
Yesware platform help — email tracking, campaigns, templates, Prospector, Meeting Scheduler, Salesforce integration, reporting. Use when Yesware tracking isn't showing opens, campaigns aren't sending to recipients, templates aren't personalizing correctly, Prospector search returns irrelevant leads, Meeting Scheduler links aren't working, or the Salesforce sync isn't logging activities. Do NOT use for building prospect lists (use /sales-prospect-list), enriching contacts (use /sales-enrich), designing cadence strategy (use /sales-cadence), cross-platform deliverability (use /sales-deliverability), meeting scheduling strategy (use /sales-meeting-scheduler), or email tracking strategy (use /sales-email-tracking).
Save the current Codex, Claude Code, or Pi conversation for later by recording a concise summary and exact resume command in ~/projects/session-resumes.md and on the macOS clipboard. Use when asked to bookmark, store, or save an agent session for resumption.
Install, configure, and troubleshoot Scalar API Reference in an application, including framework integrations, API description loading, authentication, themes, and migration from Swagger UI or Redoc. Use for embedded or self-hosted references, not hosted Scalar Docs site configuration or standalone API Client development.
Plan safe database schema evolution and zero-downtime change rollout for Kotlin plus Spring systems using Flyway, Liquibase, or equivalent migration tooling. Use when changing tables, columns, constraints, indexes, or data shape in systems with live traffic, rolling deploys, large datasets, or backward-compatibility requirements between old and new application versions.
Polishes academic English paragraph by paragraph, reviewing grammar, word choice, voice, coherence, and sentence structure. Outputs revision suggestions alongside polished text. Triggered by phrases like 'polish this paragraph,' 'check the grammar,' 'rewrite in academic English,' or keywords like manuscript editing, SCI polishing, and journal submission editing.
Use when the user wants TikTok research or workflow guidance for lead generation, influencer discovery, brand monitoring, competitor analysis, content analytics, trend research, or audience analysis, including account analysis, creator discovery, video inspection, comment scraping, transcript extraction, hashtag or song research, and TikTok Shop or product research.
Use when surveying documented security prior art for a product BEFORE it is built — deriving a threat-vocabulary map (translating a product's surfaces into the terms security corpora index), executing one search angle across weakness and attack-pattern taxonomies (CWE, CAPEC, ATT&CK), vulnerability registries (CVE/NVD, OSV, GitHub Advisory), exploitation-evidence catalogs (KEV, EPSS, Exploit-DB), vendor advisories (CSAF/VEX), incident corpora (VERIS) and control standards (OWASP ASVS, Top 10, MASVS) — or deep-reading ONE source item into an extraction whose evidence tier carries its receipts. Produces schema-validated artifacts with status-typed coverage records and mandatory zero-hit cells. Keywords: security prior art, threat research, vulnerability survey, attack patterns, CVE, CWE, CAPEC, OWASP, KEV, EPSS, advisories, supply chain. Covers the SEARCH, EXTRACT and SYNTHESIS waves.
World-class data engineering skill for building scalable data pipelines, ETL/ELT systems, and data infrastructure. Expertise in Python, SQL, Spark, Airflow, dbt, Kafka, and modern data stack. Includes data modeling, pipeline orchestration, data quality, and DataOps. Use when designing data architectures, building data pipelines, optimizing data workflows, or implementing data governance.
SEO content brief creation with keyword research, search intent analysis, and content structure. Covers SERP analysis, heading hierarchy, word count targets, and internal linking strategy. Use for: content briefs, SEO writing, blog strategy, content planning, keyword targeting. Triggers: seo content brief, content brief, seo brief, keyword research, search intent, content strategy, blog brief, seo writing, content planning, keyword targeting, serp analysis, content outline, seo article, blog seo
Senior-architect workflow for creating, editing, auditing, and monitoring SEO, AEO/GEO, LLM-readable, and AI-agent-friendly websites. Use when the user asks about SEO, technical SEO, organic visibility, AI search visibility, ChatGPT/Claude/Perplexity/Gemini readiness, robots.txt, sitemap.xml, llms.txt, schema.org/JSON-LD, canonical/noindex rules, crawl/indexation issues, Search Console/Bing Webmaster monitoring, server-log bot tracking, or making a site discoverable, quotable, machine-readable, and usable by AI agents.
Find quick-win SEO content opportunities by comparing your site's existing content against competitor keyword rankings. Chains site-content-catalog and seo-domain-analyzer to build a content inventory, then identifies gaps — topics competitors rank for that you don't cover yet. Outputs a prioritized list of posts to write or update. Use when a seed/Series A team wants to start winning organic traffic without guessing.
Validate SEO and LLM-readability claims against live HTML, local fixtures, and generated artifacts. Use this skill when the user asks to prove whether title, meta description, canonical, hreflang, JSON-LD, NewsArticle.image, OpenGraph, Twitter cards, RSS autodiscovery, robots.txt, llms.txt, sitemap, news-sitemap, crawler access, or performance evidence is actually present, and when subjective audits must become timestamped pass/fail reports.
Writes a multichannel cold outreach sequence (email + LinkedIn) for ONE hypothesis: ICP x anchor (signal / data-point / segment insight) x offer, for a B2B service company (custom development, outstaffing, engineering outsourcing, BIM/MEP, GIS). Refuses to write copy on a base with no anchor, sizes the campaign against real sending capacity, writes the email track (5 touches) and the LinkedIn track (3 touches), separate copy for the decision-maker and the champion, interest-only CTAs, then attaches the measurement plan with honest denominators and a self-check. Use when asked "write a cold sequence", "cold email sequence", "LinkedIn outreach sequence", "outreach for this ICP", "follow-ups for this campaign", "напиши сіквенс", "холодний лист", "мультиканальний сіквенс". NOT for a single reply (reply-objection-handler), NOT for analysing replies received (reply-audit), NOT for warm or inbound follow-up. Absorbed the standalone multichannel-sequence skill on 2026-09-22.
Collect and normalize search-demand inputs for public site projects before semantic-core work. Use when a UI/UX or SEO project needs seed keywords, SERP snapshots, autocomplete ideas, People Also Ask, related searches, or a dry-run keyword harvest with approval-gated external search APIs.
Configure SERP/search-demand source settings before keyword harvesting. Use when a UI/UX, SEO, or site project needs a user-facing source setup gate, OpenSERP self-host settings, proxy provider/API-key fields such as AKE, checkbox selection of Google/Yandex/Bing/DuckDuckGo/Ecosia/Baidu/manual sources, paid-proxy/budget limits, approval notes, or preflight checks before `serp-keyword-harvester` sends external queries.
Analyze credential-free public website monitoring evidence from server access logs, HTTP fetches, robots/llms/sitemap checks, and exported summaries while protecting raw IP and private query data. Use this skill when the user asks whether crawlers or AI bots reached a site, whether public SEO/LLM discovery files respond, or how to separate observed facts from unknown Search Console, rank, analytics, or citation claims.
Use when preparing server provisioning plans, IaC drafts, SSH hardening, users, firewalls, backups, monitoring, and rollback. Dry-run by default; do not create, mutate, or destroy production servers without explicit approval.
Use when choosing hosting/server architecture for a site or app: static hosting, VPS, PaaS, CDN, region, cost assumptions, scaling, security, and ops tradeoffs. Advisory only; do not provision servers or create paid resources without explicit approval.
Summarize the current session for a fresh reader, save it as an immutable handoff, or resume from a saved one. Use when the user asks to summarize current work, compact context, hand off, save continuity notes, resume from a handoff, or list available handoffs. Do not use to summarize an unrelated document.
Restores full context when user says "hi-ai" or starts a new conversation. Searches project files, loads memory indexes, reads session state, and creates visual dashboard showing current project, recent decisions, active blockers, and quick actions. Use when user says "hi-ai", "continue", "restore context", or starts a fresh conversation.
Orchestrate any code change from requirements to review-ready branch — scope-calibrated from small fixes to full features. Composes /spec, /implement, and /research with depth that scales to the task: lightweight spec and direct implementation for bug fixes and config changes, full rigor for features. Produces tested, locally reviewed, documented code on a feature branch. The developer pushes the branch and creates the PR. Use for ALL implementation work regardless of perceived scope — the workflow adapts depth, never skips phases. Triggers: ship, ship it, feature development, implement end to end, spec to PR, implement this, fix this, let's implement, let's go with that, build this, make the change, full stack implementation, autonomous development.
Use when the user wants to manage discount activities on a shoplazza store through the CLI — promotional campaigns, coupon codes, flash sales, buy-X-get-Y offers, rebates / tiered satisfy-N-get-M discounts, free-shipping codes, M-for-N (Nth-item-off) discounts, discount stacking / combination rules, or coupon (voucher) campaigns. Triggers include 满减 / 折扣码 / 优惠码 / 闪购 / 满X减Y. NOT gift cards (redeemable store credit → shoplazza-products `gift-cards`). NOT showing a sale inside a theme card / 首页促销卡片 (→ shoplazza-themes).
Store-level config and content for a Shoplazza store — use for: shop info/settings (店铺信息 / 店铺设置 / 主域名 / 币种 / 客服邮箱 / customer email); sales and traffic analytics (销量 / 销售额 / 流量 / 流量渠道 / 搜索词 / 报表 / 数据分析 / analytics / PV UV / conversion / SKU 排行 / best-selling SKU); media library and file uploads (素材库 / 媒体库 / 上传文件 / upload file — store assets, NOT product images); metafields / 元字段 / 自定义字段 — ALL metafields live HERE, including ones ON products / orders / customers (给商品加字段); blogs and articles (博客 / 文章 / blog post); custom storefront pages (自定义页面 / 关于我们 / About Us / policy page); navigation menus (导航菜单 / 菜单项 / menu items); URL redirects (重定向 / 301 / URL 跳转); markets (市场 / 多市场 / 发布到日本市场); store languages (语言 / 多语言 / 翻译 / 开通日语); real-time rate carrier services (实时运费报价 / 承运商 / carrier service). NOT product catalog / 商品图片 (→ shoplazza-products); NOT 优惠码 (→ shoplazza-discounts); NOT order search / 订单统计 / 物流查询 (→ orders domain); NOT theme editing / 装修 / page templates (→ shoplazza-themes).
Interview a founder or senior marketer one question at a time, mine current work and owned proof for net-new short-form video ideas, and return a ranked table with one five-second overlay hook, virality and three-second-hook scores, exactly three talking bullets, a complete payoff, and a mapped CTA. Use for Instagram Reels, TikTok, YouTube Shorts, LinkedIn video, founder-led content planning, hook development, content-day production queues, or turning active AI, marketing, and operating work into credible short-form concepts.
Keep a reviewable decision trail for long-running or unattended work: a TSV log with one row per decision (what, why, evidence, result). Local by default; commit it when a reviewer needs the trail to trust the result. Use for /show-me-your-work, autonomous or multi-phase runs, or work a human reviews after stepping away.
Builds a 50-trigger signal catalog for one niche, scores every signal on a 5-factor weighted model, and bundles the signals that cannot reach test volume alone. Use when the user says "каталог сигналів", "signal catalog", "які сигнали брати", "по чому таргетити", "build triggers for [niche]", or is choosing what to detect before building a prospect list. Produces the raw material for hypotheses — not the hypotheses themselves.
Master router for signal-based outbound — runs the full path from a service page to an email addressed to a named person with a verified address, routing to the right skill at each step and enforcing the gate between them. Use when someone asks to build outbound from scratch, says "запусти аутбаунд", "run the outbound process", "де почати", "build me a campaign", "we need pipeline", or is holding one artifact (an ICP, a list, a sequence) and does not know what comes next. Also the place to start when a campaign is already running badly and you need to find which stage broke — "our outbound isn't working", "нема відповідей", "which skill do I use", "що робити далі". Start here rather than guessing which individual skill applies.
Use when a public website needs an AI assistant with source-bounded answers, RAG/content scope, injection protection, escalation, logging, rate limits, refusals, and no hallucinated product/legal/price claims. Planning or implementation handoff only; do not expose secrets or give destructive tools.
Crawl a website's sitemap and blog index to build a complete content inventory. Lists every page with URL, title, publish date, content type, and topic cluster. Groups content by category and topic. Optionally deep-reads top N pages for quality analysis and funnel stage tagging. Use before SEO audits, content gap analysis, or brand voice extraction.
Coordinate SEO, LLM-readable site architecture, UX, content, monitoring, security, and external authority work as a task-plan-driven sequence. Use this skill when the user asks to plan, execute, validate, or route multi-skill website growth work; asks what to do next across semantic core, URL structure, internal linking, schema, llms.txt, UX journeys, analytics, citation monitoring, or white-hat link placement; or wants a central architect that preserves evidence, alarms, handoffs, and tests.
Create or refactor Ship Faster-style skills (SKILL.md + references/ + scripts/). Use when adding a new skill, tightening trigger descriptions, splitting long docs into references, defining artifact-first I/O contracts, or packaging/validating a skill.
Design, build, and maintain standalone AI skills from a canonical source package, with prose for judgment and declared tools for exact work, built deterministically into skill folders. Use when creating, changing, splitting, testing, or delivering an AI skill as a source package (`skill-package.json`), including starting a project's first one, or when a built skill's delivery or evidence is in question.
Validates all interactive skills in this repo against the Agent Skills spec, project conventions, and structural requirements. Runs quick_validate.py, checks line limits, verifies cross-references, and tests hook scripts. Use when skills have been added or modified and you want to verify everything passes before committing or submitting.
For searching financial markets, securities, listed-company fundamentals, prices, candlestick charts, disclosure filings, financial news, A-share data, Hong Kong stocks, or global tickers, using yfinance, mootdx, API scripts, or browser-use.
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.