Skills
100,344 packaged capabilities and playbooks for agents. Install any of them with one command.
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When the user wants to build or improve a sales bot's ability to recognize and reinforce buying signals. Also use when the user mentions "buying signals," "purchase intent," "interest indicators," "signal amplification," or "intent reinforcement."
When the user wants to build or improve a sales bot's ability to offer and confirm specific callback times when prospects say "call me later." Also use when the user mentions "scheduling callbacks," "call me back," "booking calls," "callback handling," or "follow-up scheduling."
Senior Information Security Manager specializing in ISO 27001 and ISO 27002 implementation for HealthTech and MedTech companies. Provides ISMS implementation, cybersecurity risk assessment, security controls management, and compliance oversight. Use for ISMS design, security risk assessments, control implementation, and ISO 27001 certification activities.
Guides pre-writing planning for academic papers with 4 structured steps: story design (task-challenge-insight-contribution-advantage), experiment planning (comparisons + ablations), figure design (pipeline + teaser), and 4-week timeline management. Includes counterintuitive planning tactics (write a mock rejection letter to identify weaknesses before writing, narrow before broad claims, design ablations first). Use when: user wants to plan a paper before writing, design story/contributions, plan experiments, create figure sketches, set a writing timeline, or write a pre-emptive rejection letter for planning purposes. Do NOT use for actual writing (use paper-writing), running experiments (use experiment-pipeline), self-reviewing a finished draft (use paper-review), or finding research problems (use research-ideation).
When the user wants to build or improve a sales bot's ability to dynamically insert names, company details, and relevant context into conversations. Also use when the user mentions “dynamic personalization,” “merge fields,” “personalized outreach,” “customizing messages at scale,” or “personalization variables.”
Design, plan, and analyze A/B tests with statistical rigor. Use when the user asks about A/B testing, split testing, experiment design, statistical significance, sample size calculation, test duration, multivariate testing, or conversion experiments. Trigger phrases include “A/B test,” “split test,” “experiment,” “statistical significance,” “sample size,” “test duration,” “which version wins,” “conversion experiment,” “hypothesis test,” “variant testing”
Use when the user wants to build or improve a sales bot's ability to send brochures, videos, floorplans, or other media contextually during conversations. Also use when the user mentions “sending attachments,” “media sharing,” “document delivery,” “sending brochures,” or “content delivery.”
Use for data strategy decisions: training models on customer data, warehouse vs lakehouse vs mesh, valuing data for a raise or M&A, or data hiring order. Runs ai_training_data_audit.py, data_product_strategy_picker.py and data_asset_valuator.py.
When the user wants to build or improve a sales bot's ability to respect opt-outs, DNC lists, and regulatory requirements like TCPA and ACMA. Also use when the user mentions "compliance," "opt-out handling," "TCPA," "ACMA," "DNC lists," "unsubscribe," or "regulatory requirements."
Designs relational and document database schemas from requirements or an existing app, including tables and collections, keys, relationships, constraints, indexes driven by real query patterns, ERDs, and reversible migration scripts. PostgreSQL (including Supabase) is the default; MySQL, SQLite, and MongoDB are also supported. Use when the user wants to model data for a new app or feature, review or fix an existing schema, choose keys or indexes, plan multi-tenancy, normalize or denormalize, or write CREATE TABLE statements or migrations—even if they just describe their app and ask “how should I store this”. For moving data between database providers, use database-migrator.
Use when the user wants to build or improve a sales bot's ability to gracefully end conversations with poor-fit prospects. Also use when the user mentions “disqualification,” “not a fit,” “poor fit messaging,” “declining prospects,” or “graceful rejection.”
Use when the user wants to build or improve a sales bot's ability to extract key data points (budget, timeline, company size, location, requirements) from unstructured prospect responses. Also use when the user mentions “extracting data,” “parsing responses,” “pulling out details,” “structured data from conversations,” or “NER for sales.”
Records visual proof while testing UI behavior—the agent tests the app hands-on via computer use while a screen recording with structured test/assertion annotations captures the session—then posts the video and a results summary to the requested destination. Use when changed runtime behavior needs observable verification, including headless environments (scripted screenshots and probes) and non-UI changes (measured numbers, output pairs).
Transform raw data from CSVs, Google Sheets, or databases into executive-ready reports with visualizations, key metrics, trend analysis, and actionable recommendations. Creates data-driven narratives for leadership. Use when users need to turn spreadsheets into executive summaries or board reports.
Integrate Firecrawl `/scrape` into product code for single-page extraction. Use when an app already has a URL and needs markdown, HTML, links, screenshots, metadata, or structured page output. Prefer this skill over broader crawl patterns when the feature is page-level.
Fund investment assistant. Check real-time fund estimates, NAV, and price changes; search funds by name or code; manage portfolios (add or remove holdings, record transactions, calculate returns); view market indexes, capital flows, and northbound funds; import and export holding data. Supports multi-user data isolation. Trigger terms: funds, NAV, valuation, holdings, returns, regular investment, market data, northbound funds, CSI 300
Build integrations with Google Workspace APIs (Gmail, Calendar, Drive, Sheets, Docs, Chat, Meet, Forms, Tasks, Admin SDK). Covers OAuth 2.0, service accounts, rate limits, batch operations, and Cloudflare Workers patterns. Use when building MCP servers, automation tools, or integrations with any Google Workspace API, or troubleshooting OAuth errors, rate limit 429 errors, scope issues, or API-specific gotchas.
Select semantically appropriate icons for websites using Lucide, Heroicons, or Phosphor. Covers concept-to-icon mapping, React/HTML templates, and tree-shaking patterns. Use when: building feature sections, service grids, contact info, navigation, or any UI needing icons. Prevents emoji usage, ensures consistency.
Use when the user wants to build or improve a sales bot's ability to avoid making claims that create liability. Also use when the user mentions “compliance,” “legal risk,” “claim avoidance,” “regulated industries,” or “liability prevention.”
Runs an evidence-based health audit of this skills marketplace repo—code safety, docs/SSOT, security/PII, PR/issue triage, and manifest integrity—via a parallel workflow, then verifies findings by priority. Use for 全面体检 / 检查仓库状态 / 审计一下仓库, a pre-release sweep, or “is this repo OK” even without saying “workflow.” Not for building marketplace.json (use marketplace-dev) or cache drift (use skill-governance)
When the user wants to build or improve a sales bot's ability to confirm meetings and reduce no-shows. Also use when the user mentions "meeting confirmation," "calendar reminders," "no-show reduction," "appointment reminders," or "meeting attendance."
When the user wants to build or improve a sales bot's ability to manage sender reputation and ensure messages get delivered. Also use when the user mentions "deliverability," "spam prevention," "sender reputation," "email warmup," or "domain reputation."
Structured OSINT investigations — people lookup, company intel, investment due diligence, entity/threat intel, domain recon, and organization research using public sources within an ethical authorization framework. Use when dealing with OSINT, due diligence, background checks, researching people, company intelligence, investigations, company/domain/entity/organization lookups, threat intelligence, or discovering OSINT sources.
When the user wants to build or improve a sales bot's ability to match message length to channel and prospect behavior. Also use when the user mentions "message length," "response calibration," "message sizing," "brevity," or "message formatting."
Use when a UE5 task involves materials or textures: a master material and instances for a kit, Substrate or legacy, Blendable vs Adaptive GBuffer, glass, emissive screens, decals, edge wear and dirt, landscape layers and RVT, toon or cel shading, "too many shaders" or shader permutations, static switches, usage flags, texture compression (BC7, normal maps, ORM packing, sRGB), texture memory, or "is this material expensive".
Use when building or fixing an Unreal Engine 5 level or open world: World Partition, OFPA, Data Layers, Level Instances, Packed Level Actors, HLOD, landscape size, heightmap import or clipping, edit layers, terrain material rules, foliage and grass, a PCG forest or rock scatter, runtime GPU grass, Nanite and tessellation choices, modular kits, a river or village, streaming pop-in, cells not loading, landscape black spots, "PCG shows nothing in the editor", or a world too heavy to hand to lighting.
Optimize signup and registration conversion funnels. Use when asked to improve signup rates, reduce form abandonment, audit registration flows, or optimize conversion funnels. Trigger phrases: "signup optimization", "registration flow", "form conversion", "signup CRO", "reduce abandonment", "signup funnel", "form optimization", "conversion rate optimization", "registration page".
Use when asked to “thinking in bets,” “make decisions under uncertainty,” “think probabilistically,” “avoid resulting,” “separate decision quality from outcomes,” or “reduce bias in decisions.” Helps make explicit bets and evaluate decisions on process, not results. The Thinking in Bets framework (from Annie Duke) applies poker strategy to business and life decisions.
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.