Skills
97,501 packaged capabilities and playbooks for agents. Install any of them with one command.
Data & databases
Create a database migration to add a table, add columns to an existing table, add a setting, or otherwise change the schema of Ghost's MySQL database. Use this skill whenever the task involves modifying Ghost's database schema — including adding, removing, or renaming columns or tables, adding new settings, creating indexes, updating data, or any change that requires a migration file in ghost. Also use when the user references schema.js, knex-migrator, the migrations directory, or asks to "add a field" or "add a column" to any Ghost model/table. Even if the user frames it as a feature or Linear issue, if the implementation requires a schema change, this skill applies.
Use for PhD-level expertise in data science, statistics, and machine learning: rigorous statistical analysis, experimental design, causal inference, advanced modeling, research methodology, or data science project leadership. Load when the user asks about statistical methods, experimental design, model selection, A/B testing, hypothesis testing, power analysis, regression, causality, Bayesian analysis, or research methodology. For insurance, actuarial, claims, reserving, solvency, credibility, tail-risk, or financial-risk statistical modeling, use `actuarial-risk-modeling`; for deterministic operating and SaaS financial models, use `financial-modeling`. Do not use this skill for unrelated requests; route to the nearest named specialist.
Skill for extracting and writing content in multiple Excel formats, using the calamine library to handle .xls, .xlsx, .xlsm and other formats. Use this skill whenever the user needs to parse Excel files, extract tabular data, convert Excel to text format, analyze Excel content, batch-process Excel files, create new Excel files, or update existing Excel files. Applies to scenarios such as data extraction, report analysis, content review, and data export.
Financial data toolkit for US market analysis. Provides scripts to fetch real-time stock data (yfinance), SEC filings and insider trades (EDGAR), financial statement calculators (DuPont, Z-Score, M-Score, F-Score), portfolio analytics (VaR, stress testing, health scoring), multi-factor screening, and macro indicators (FRED). Use when you need live US market data to ground investment analysis. All data sources are free — no API keys required.
Data persistence patterns in Go covering raw SQL with sqlx/pgx, ORMs like Ent and GORM, connection pooling, migrations with golang-migrate, and transaction management. Use when implementing database access, designing repositories, or managing schema migrations.
Standardizes all click-related IDs and CSS classes across website for clean analytics tracking. Use when users want to "standardize analytics classes", "clean up tracking IDs", "prepare DOM for GTM", "fix analytics naming", or "make tracking consistent". Scans entire codebase (HTML/JSX/TSX/Vue) and applies consistent naming convention - IDs as "cta_{location}_{action}" and classes as "js-track js-{category} js-{action} js-{location}". Acts as senior frontend engineer ensuring scalable GA4/GTM implementation.
Quantifies market breadth using TraderMonty's public CSV data. Generates a composite score from 0–100 across 6 components (100 = healthy). No API key required. Use when the user asks about market breadth, participation rate, advance-decline health, whether a rally is broad-based, or general market health.
Discovers all businesses of a given type in any geography using Nimble WSAs. Two modes: Discovery finds businesses from scratch; Audit compares a user's existing list (Google Sheet, CSV, inline) against fresh discovery, categorizing entries as matched, discovered-only, or reference-only. Vertical presets (Healthcare, SaaS, Restaurants, Legal, Auto/Home) auto-select WSA routing. Triggers: "find all X in Y", "build a list of", "market sizing", "account universe", "how many X in Y", "TAM for", "discover all", "audit my list", "compare against", "what am I missing", "gap analysis", "verify my business list", "prospect list". Do NOT use for competitor monitoring — use competitor-intel instead. Do NOT use for company deep dives — use company-deep-dive instead. Do NOT use for neighborhood-level exploration with social enrichment — use local-places instead.
Run MassGen experiments and analyze logs using automation mode, logfire tracing, and SQL queries. Use this skill for performance analysis, debugging agent behavior, evaluating coordination patterns, and improving the logging structure, or whenever an ANALYSIS_REPORT.md is needed in a log directory.
Execute database operations via Supabase MCP (query/write/migration/logs/type generation). Triggers: query/statistics/export/insert/update/delete/fix/backfill/migrate/logs/alerts/type generation. Does not trigger for: pure architecture discussion or code planning. Write operations require confirmation; UPDATE/DELETE without WHERE is refused.
Use when the user needs to extract data from PDFs, work with scanned documents, or manipulate PDF files. Triggers include: "extract text from PDF", "convert PDF to text/CSV/images", "scan/OCR this document", "merge/split/rotate PDF", "fill PDF form", "PDF is blank/empty" (likely scanned), or any mention of .pdf files requiring data extraction or transformation. Also use for invoices, receipts, forms, contracts, reports, or any document where structured data (text, tables, form fields) needs to be extracted.
Full-site crawling, scraping, and site mapping via Firecrawl MCP. Use when user says "crawl site", "map site", "full crawl", "find all pages", "broken links", "site structure", "discover pages", "JS rendering", or needs site-wide analysis.
Create or read Statsig dashboards through the Console API. Use when building a valid `POST /console/v1/dashboards` body, reading `GET /console/v1/dashboards/{id}` into a create-compatible shape, or appending or replacing dashboard widgets through the related widget endpoints.
Builds Python Tilebox workflows for Earth observation and geospatial processing, including satellite imagery queries, AOI and time-series pipelines, mosaics, spectral indices, classification, segmentation, change detection, and tiled ML or object detection. Use when implementing or modifying this processing, including when Tilebox is not named and no other execution platform is established.
Direct TMDL file authoring and BIM-to-TMDL conversion for semantic models in PBIP projects. Automatically invoke when the user asks to "edit TMDL", "add a measure in TMDL", "TMDL syntax", "fix formatString", "fix summarizeBy", "TMDL indentation", "convert BIM to TMDL", "add a column description", "create a calculated column in TMDL", or mentions .tmdl file editing or BIM-to-TMDL migration.
AI Trading Intelligence — live prices, 30+ technical indicators, backtesting (6 strategies), walk-forward overfitting detection, trade logs, equity curves, licensed news sentiment (Marketaux), and multi-market screener. Supports stocks, crypto, ETFs, indices, Turkish (BIST), and Egyptian (EGX) markets.
Screen US stocks for high-quality dividend opportunities combining value characteristics (P/E ratio under 20, P/B ratio under 2), attractive yields (3% or higher), and consistent growth (dividend/revenue/EPS trending up over 3 years). Supports two-stage screening using FINVIZ Elite API for efficient pre-filtering followed by FMP API for detailed analysis. Use when user requests dividend stock screening, income portfolio ideas, or quality value stocks with strong fundamentals.
WordPress ACF and content modeling review. Use when reviewing Advanced Custom Fields usage, field group architecture, CPT and taxonomy design, options pages, repeaters, flexible content, block-bound field groups, meta storage patterns, or when user mentions "ACF", "field groups", "flexible content", "repeater", "custom post type design", "taxonomy design", "content model", "relationship fields", "ACF JSON", "options page", or "meta query performance". Detects schema drift, weak content modeling, brittle field naming, and performance issues in meta-heavy WordPress builds.
Conducts comprehensive, systematic literature reviews across multiple academic databases (PubMed, arXiv, bioRxiv, Semantic Scholar), with PRISMA 2020 flow tracking, study screening (title/abstract and full-text), evidence-table extraction, and risk-of-bias assessment (RoB 2, ROBINS-I, AMSTAR 2), producing professionally formatted markdown documents and PDFs with verified citations in multiple styles (APA, Nature, Vancouver). Use when running a systematic or scoping literature review, research synthesis, or broad literature search, building a PRISMA flow diagram, screening studies, extracting an evidence table, or assessing risk of bias across biomedical, scientific, and technical domains. For quantitative pooling of effect sizes (forest/funnel plots) use alterlab-meta-analysis; for an open-ended multi-agent investigation, fact-check, or Socratic research-question work use alterlab-deep-research. Part of the AlterLab Academic Skills suite.
Perform full-dimensional penetrating analysis of Amazon competitor listings, including copy logic, review analysis, keyword analysis, and market dynamics. After analysis, automatically save a Markdown report to the reports/ directory. Invoke when user uses /amazon-analyse command with a product ASIN.
Generate structured narrative text visualizations from data using T8 Syntax. Use when users want to create data interpretation reports, summaries, or structured articles with semantic entity annotations. T8 is designed for unstructured data visualization where T stands for Text and 8 represents a byte of 8 bits, symbolizing deep insights beneath the text.
Runs the Azure SQL Database container locally (Private Preview): the real PaaS engine where SERVERPROPERTY('EngineEdition') returns 5. This is NOT the SQL Server image mcr.microsoft.com/mssql/server. Use when a user wants to "run Azure SQL locally", "add a local SQL database", "add SQL Server to my docker compose", "spin up a local mssql container", "local SQL for development or CI", "connect with sqlcmd", "use Podman for SQL", "SQL container won't start", "Microsoft Entra authentication on the container", "MSSQL_AAD_CLIENT_ID", or asks "what's the connection string". Use even when the user does not name the container. If you were about to use mcr.microsoft.com/mssql/server, stop and use this skill instead. Hub skill: owns the shared references and routes to the task skills for compose, CI, seeding, vectors, and connection strings.
Drift analysis for Pulumi infrastructure costs. Runs finfocus to compare actual vs projected spend, flags drifting resources against configurable thresholds, generates likely-cause explanations with investigation prompts, and tracks drift trends over time. Produces a terminal summary and COST_DRIFT.md report. Use when investigating cost overruns, validating projections against reality, or monitoring spend drift in CI.
Database access patterns for performance. Separate read/write models, avoid N+1 queries, use AsNoTracking, apply row limits, and never do application-side joins. Works with EF Core and Dapper. Use when designing data access layers, optimizing slow database queries, choosing between EF Core and Dapper, or avoiding common performance pitfalls.
Use this skill when users want to run any workload on Hugging Face Jobs infrastructure. Covers UV scripts, Docker-based jobs, hardware selection, cost estimation, token authentication, secrets management, timeout configuration, and result persistence. Designed for general-purpose compute workloads, including data processing, inference, experiments, batch jobs, and any Python-based tasks. Invoke for tasks involving cloud compute, GPU workloads, or when users mention running jobs on Hugging Face infrastructure without local setup.
Converts CSV/TSV inputs into Infrahub object YAML and loads them onto a fresh branch. Handles a single file, a folder of files, an explicit list of paths, and one-big-denormalized-sheet exports. TRIGGER when: importing CSV, loading CSV/TSV into Infrahub, ingesting spreadsheet data, converting CSV to Infrahub objects, splitting a denormalized CSV across multiple kinds, re-running an import after changing a column mapping, debugging why a row fails to convert or load. DO NOT TRIGGER when: running `infrahubctl load` against an LDJSON dump (different format and tool), designing or modifying schemas (this skill is read-only against the schema and fails closed on unmapped columns), exporting data from Infrahub (use `infrahubctl object get -o csv` for single-kind export), or ingesting JSON/XLSX (v1 is CSV+TSV only).
Extract invoice data from images or text descriptions and generate a categorized Excel expense report. Supports receipt photos, scanned invoices, and manual text input. Auto-classifies into: business entertainment (客户餐费), travel-transport (机票/火车票/打车), travel-accommodation (酒店), travel-meals, office supplies, communication, and other. Use when the user mentions "发票报销", "expense report", "报销单", "发票整理", "invoice", "报销汇总", "发票分类", "reimbursement", or has invoice images to process.
Write JavaScript code in n8n Code nodes. Use when writing JavaScript in n8n, using $input/$json/$node syntax, making HTTP requests with this.helpers / the $helpers global, working with dates using DateTime, troubleshooting Code node errors, choosing between Code node modes, or doing any custom data transformation in n8n. Always use this skill when a workflow needs a Code node — whether for data aggregation, filtering, API calls, format conversion, batch processing logic, or any custom JavaScript. Covers SplitInBatches loop patterns, cross-iteration data, pairedItem, and real-world production patterns. Also use when asked why a Code node or workflow is slow, which execution mode is faster, or how to cut per-item overhead on large datasets. EXCEPTION — for the AI-agent-callable Custom Code Tool (@n8n/n8n-nodes-langchain.toolCode, a tool attached to an AI Agent), use the n8n-code-tool skill instead; it has a different runtime contract.
Use when you are about to write or edit a comment in PL/SQL you are changing, or in a .sql deliverable headed for the database. One line, one fixed shape, and anything longer goes where it belongs instead. It fires on the act of commenting rather than on a request — catching yourself opening a second comment line above one statement is the trigger
Use when a Roblox game saves or loads player data, or when players report data not saving, lost progress, rollbacks, duplicated items or a purchase granted twice. Triggers: DataStoreService, UpdateAsync, SetAsync, BindToClose, ProfileStore, ProfileService, DataStore2, session locking, data schema or migration, Developer Product ProcessReceipt, player trading, OrderedDataStore leaderboards, MemoryStore, MessagingService, TeleportService and reserved servers, DataStore budgets and throttling (errors 301 to 306), 'You must publish this place to the web to access DataStore', and testing data code in an unpublished place.
Python-based workflow manager for reproducible, scalable pipelines. Define rules with file-based dependencies; Snakemake resolves execution order and parallelism. Runs local, SLURM, LSF, AWS, GCP via profiles; per-rule conda/Singularity envs. For NGS pipelines, ML training, and multi-step file processing. Use Nextflow for Groovy dataflow or nf-core integration.
Generate your Team Performance Dashboard from your La Growth Machine data: a head-of-sales cockpit that ranks each sender (rep) on reply rate, your success event (signups/meetings/deals) and conversion, surfaces hot leads going cold, and turns your best reps' campaigns into a coaching playbook for the rest. Pulls only YOUR live LGM data into one sortable all-KPI team table plus a value (€) layer, classifies real replies, and renders a live artifact. This is the PER-REP team view, not the per-campaign weekly-performance-advisor. Use when a head of sales, SDR manager, GTM engineer or RevOps wants per-member outbound stats, who converts best and why, which replies are unanswered, or what to clone across the team. Triggers on: 'stats by member', 'team performance dashboard', 'per-rep outbound', 'who converts best', 'weekly team performance', 'sales team cockpit', 'coach my SDRs', 'per-identity reply rate'. First run does a short setup (~10-15 min); later runs just rebuild. Maintained by La Growth Machine.
Analyzes market breadth using Monty's Uptrend Ratio Dashboard data to diagnose the current market environment. Generates a 0–100 composite score from 5 components (breadth, sector participation, rotation, momentum, historical context). Use when asking about market breadth, uptrend ratios, or whether the market environment supports equity exposure. No API key required
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.