Skills
100,344 packaged capabilities and playbooks for agents. Install any of them with one command.
All
Build with D1 serverless SQLite database on Cloudflare's edge. Use when: creating databases, writing SQL migrations, querying D1 from Workers, handling relational data, or troubleshooting D1_ERROR, statement too long, migration failures, or query performance issues. Prevents 14 documented errors
Comprehensive Cloudflare account management for deploying Workers, KV Storage, R2, Pages, DNS, and Routes. Use when deploying cloudflare services, managing worker containers, configuring KV/R2 storage, or setting up DNS/routing. Requires CLOUDFLARE_API_KEY in .env and Bun runtime with dependencies installed.
Research competitors and compare positioning, messaging, content strategy, and market presence. Use when analyzing a competitor, building battlecards, identifying content gaps, comparing feature messaging, or preparing competitive positioning recommendations
Write copy engineered to drive one specific action — landing pages, sales pages, opt-in pages, ads, promotional emails — using an eight-part direct-response architecture (hook, problem, mechanism, solution, proof, objections, CTA, urgency). Use when the user says 'write my landing page / sales page / ad', 'this page isn't converting', 'rewrite my homepage copy', 'write copy for my lead magnet page', or any request for persuasive copy with a measurable action at the end. Produces the full copy draft, section-labeled against the architecture, plus hook alternatives and a conversion checklist.
Expert patterns for branching dialogue systems including dialogue graphs (Resource-based), character portraits, player choices, conditional dialogue (flags/quests), typewriter effects, localization support, and voice acting integration. Use for narrative games, RPGs, or visual novels. Trigger keywords: DialogueLine, DialogueChoice, DialogueGraph, dialogue_manager, typewriter_effect, branching_dialogue, dialogue_flags, localization, voice_acting.
Use when looking up journal impact factors (JCR IF), checking a journal's impact factor by name, comparing IF across journals, or answering questions about "影响因子" / "impact factor" / "IF". Triggers on "impact factor", "journal IF", "影响因子", "JCR", "IF score", "journal rank", "which journal has higher IF", "what is the IF of". PROACTIVELY USE when user mentions journal prestige, publication venue quality, or manuscript submission target evaluation.
Search and browse product listings across multiple international eBay sites. Activate when the user mentions eBay product search, eBay listing lookup, eBay price comparison, eBay market browsing, sold items, eBay auction search, eBay product research, eBay search, eBay products, eBay pricing, eBay competitors, sold items, eBay auctions, or eBay market analysis. Also activate even if the user does not explicitly mention "eBay" whenever their request involves searching for products on eBay, comparing eBay prices, finding completed listings, or analyzing eBay market data.
This skill should be used for persistent semantic memory in agent systems: cross-session knowledge retention, entity tracking, temporal validity, graph or vector retrieval, memory consolidation, and memory benchmark selection. Route file-backed scratchpads to filesystem-context, handoff summaries to context-compression, and token-efficiency tactics to context-optimization
Create diagrams and visualizations using Mermaid syntax. Use when generating flowcharts, sequence diagrams, class diagrams, entity-relationship diagrams, Gantt charts, or any visual documentation. Triggers on Mermaid, flowchart, sequence diagram, class diagram, ER diagram, Gantt chart, diagram, visualization.
Retrieve gene expression and omics datasets from ArrayExpress and BioStudies with gene disambiguation and quality assessment. Use for finding RNA-seq/microarray datasets by organism/tissue/condition, comparing across studies (case-control, time-series, dose-response), and assessing dataset suitability before downloading. Always uses English search terms.
Statistical modeling — linear/logistic/ordinal/Poisson regression, ANOVA, Kruskal-Wallis, chi-square, Mann-Whitney, Cox survival, spline fits (R `ns()`), odds ratios, Cohen's d, F-statistic, and p-value computation. Specializes in clinical-trial AE analysis (SDTM DM/AE), severity ordinal regression, and per-feature statistical workflows.
Use when you need to design, review, or improve REST APIs with Spring Boot — including HTTP methods, resource URIs, status codes, DTOs, versioning, deprecation and sunset headers, content negotiation (JSON and vendor media types), ISO-8601 instants in DTOs, pagination/sorting/filtering, Bean Validation at the boundary, idempotency, ETag concurrency, HTTP caching, error handling, security, contract-first OpenAPI (OpenAPI Generator), controller advice, and problem details for errors. This should trigger for requests such as Review Java code for Spring Boot REST API; Apply best practices for Spring Boot REST API in Java code; Design Spring Boot REST controllers and DTOs; Add Problem Details error responses in Spring Boot REST; Improve pagination validation or idempotency in Spring APIs. Part of Plinth Toolkit
This skill should be used when the user asks "what are my balances", "how much ETH do I have", "check my wallet", "show my tokens", "portfolio value", "what tokens do I own", "NFT holdings", "how much USDC", "get token balances", "wallet contents", or any question about token balances, wallet contents, portfolio values, or NFT holdings across chains using the Bankr SDK.
Use at the start of any bug bounty hunting session, when switching targets, or when feeling lost about what to do next. Master orchestrator combining the 5-phase non-linear hunting workflow with the critical thinking framework (developer psychology, anomaly detection, What-If experiments). Routes to all other skills based on the current hunting phase. Also use when asking “what should I do next” or “where am I in the process.”
Investigate LLM spend in PostHog: total cost over time, cost by model, provider, user, trace, or custom dimension, token and cache-hit economics, and cost regressions. Use when the user asks "how much are we spending on LLMs?", "which model / user / feature is most expensive?", "why did cost spike?", wants to build a cost dashboard or alert, or pastes a trace URL and asks about its cost.
Python library for working with geospatial vector data including shapefiles, GeoJSON, and GeoPackage files. Use when working with geographic data for spatial analysis, geometric operations, coordinate transformations, spatial joins, overlay operations, choropleth mapping, or any task involving reading/writing/analyzing vector geographic data. Supports PostGIS databases, interactive maps, and integration with matplotlib/folium/cartopy. Use for tasks like buffer analysis, spatial joins between datasets, dissolving boundaries, clipping data, calculating areas/distances, reprojecting coordinate systems, creating maps, or converting between spatial file formats.
A skill for Amazon Ads store authorization and management, providing a complete authorization flow, queries for linked accounts and marketplaces, profile management, and disconnection of the current user's advertising authorization. Before creating an authorization link, confirm an account name with the user; a single authorization can automatically discover and link all available advertising profiles under that account across marketplaces (each marketplace corresponds to a profileId). Trigger this skill when the user mentions Amazon advertising authorization, Amazon Ads authorization, bulk authorization, linking or unlinking an ad account, disconnecting an ad connection, canceling advertising authorization, querying a profile list, managing authorized ad accounts, Amazon Advertising authorization, list profiles, or ad account management. Trigger it even without an explicit mention of "Amazon Ads" or "authorization" if the request involves linking Amazon advertising accounts, managing authorization relationships, or querying advertising profile lists. Authorization supports keeping the original manual flow or choosing Ziniu CLI automatic authorization.
Search and filter Amazon products using Keepa data by category, keywords, price, monthly sales, BSR, reviews, rating, brand, listing date, package dimensions, weight, and fulfillment method; view historical rankings and sales as needed. Suitable for advanced product selection, competitor filtering, new product discovery, niche market research, and multi-criteria product searches; Keepa need not be mentioned explicitly. Not for live storefront search rankings, search-term traffic trends, review text or sentiment analysis, ad management, Listing copy optimization, or inventory and supply chain queries.
Use SellerSprite’s market statistics feature to create category-node market dashboards. Includes average ratings, average prices, BSR, sales volume, seller counts, and new-product metrics for top listings, helping quickly assess market quality and competition in a category. Trigger this skill when users mention category market statistics, market selection dashboards, basic market assessment, node market quality, top-product statistics, SellerSprite market statistics, or category statistics. Trigger it even if the user does not explicitly mention "SellerSprite" as long as they want aggregated statistics by category node.
Use this skill when the user wants to organize, classify, or maintain a PARA-method second brain. Triggers include asking where to file something, distinguishing projects from areas, processing an inbox, setting up a new project, completing or archiving a project, running a monthly review, validating system structure, or finding stale/orphaned content.
Build augmented reality experiences with RealityKit and ARKit on iOS. Use when adding 3D content with RealityView, loading entities and models, placing objects via raycasting, configuring AR camera sessions, handling world tracking, scene understanding, or implementing entity interactions and gestures.
Package entire code repositories into single AI-friendly files using Repomix. Capabilities include pack codebases with customizable include/exclude patterns, generate multiple output formats (XML, Markdown, plain text), preserve file structure and context, optimize for AI consumption with token counting, filter by file types and directories, add custom headers and summaries. Use when packaging codebases for AI analysis, creating repository snapshots for LLM context, analyzing third-party libraries, preparing for security audits, generating documentation context, or evaluating unfamiliar codebases.
Use when animating characters or scenes in Godot 4.7: AnimationPlayer clips and RESET, AnimationTree state machines and blend spaces built in code, Mixamo or glTF import, loop settings, BoneMap retargeting and shared animation libraries, root motion, foot sliding, foot IK with TwoBoneIK3D or custom SkeletonModifier3D, tweens, SpringArm3D cameras, cutscenes; or when a character T-poses, slides, floats, freezes mid-blend or a transition never fires.
Generate platform-specific social post variants (Twitter/X, LinkedIn, Reddit) from one source input. Works with or without a Node.js script. Includes platform reasoning, quality review, and guardrails against cross-posting spam.
AI-driven patient-to-trial matching for precision oncology and rare-disease care. Transforms a patient's molecular profile (mutations, biomarkers, expression) and clinical state into ranked clinical-trial recommendations with evidence tiers. Searches ClinicalTrials.gov, the EU CTIS register (European/EEA trials), AND the ISRCTN registry (UK/international) plus cross-references CIViC, OpenTargets, ChEMBL, and FDA labels. Use for matching patients to trials by genotype, biomarker-driven trial selection, trial-eligibility scoring, and finding trials across the US, Europe, and the UK.
Understand and customize the local Trellis architecture inside a user project. Use when modifying .trellis plus platform hooks, settings, agents, skills, commands, prompts, workflows, the channel runtime (trellis channel), bundled runtime agents under .trellis/agents/, selectable workflow templates, registry-backed spec refresh, cross-session memory (trellis mem) generated by trellis init, or AI-facing bundled skills (trellis-channel, trellis-session-insight, trellis-spec-bootstrap) and bundled-skill auto-dispatch flow.
Apply systematic problem-solving methodologies to complex challenges. Use when the user says “guide me through structured problem solving” or “I want to crack this challenge with guided problem solving techniques.”
Re-explain the previous assistant message, or any text typed after the command, in a much simpler way. For when a reply made you go 'bro what'. Use /bro for a plain-language version of the last answer, or /bro <text> to simplify a pasted paragraph, error, email, or doc
This skill should be used when the user asks about "WebSocket in Bun", "real-time communication", "Bun.serve websocket", "ws server", "socket connections", "pub/sub", "broadcasting messages", "WebSocket upgrade", or building real-time applications with Bun
QA the omo Codex Light edition (lazycodex / packages/omo-codex) itself, in strict isolation so ONLY our plugin is exercised, never the user's real ~/.codex. The first-party method drives the real `codex app-server` against an isolated CODEX_HOME plus a LOCAL mock model (no real API call), and proves a plugin hook fired by asserting hook/started + hook/completed notifications. Also: isolated install verification, per-component hook probes, a tmux TUI smoke, and runtime log observation (RUST_LOG / logs SQLite / /debug-config). Ships tested helper scripts each with a --self-test. Use whenever someone changes anything under packages/omo-codex or wants to QA, smoke-test, verify, or debug the Codex plugin, its hooks/components, the installer/config.toml, the app-server flow, or the Codex TUI. Triggers: codex qa, qa codex, codex-qa, test codex plugin, verify codex hook, codex app-server, lazycodex qa, isolated CODEX_HOME, prove codex hook fired, codex tui test.
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.