Skills
97,905 packaged capabilities and playbooks for agents. Install any of them with one command.
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Model Context Protocol server development, tool design, resource handling, and transport configuration. Use for: mcp, model context protocol, mcp server, mcp tool, mcp resource, fastmcp, mcp transport, stdio, sse, streamable http, mcp inspector, tool handler, mcp prompt.
Memory query feature of an AI personal memory system. Retrieves memory files at each layer and combines multi-layer information to answer user questions. Use cases: (1) when the user asks "what do my memories say about XXX"; (2) when the user asks about their own habits, preferences, or values; (3) when advice needs to be based on the user's history. The skill automatically retrieves the L1-L4 layers, cites sources, and gives personalized answers grounded in memory.
Implements MercadoPago recurring subscriptions with preapproval plans in a React + Supabase Edge Functions stack. Covers the full lifecycle — creation, cancellation, plan changes, payment method changes, pause/reactivate, webhooks, and CRON sync. Use when building or modifying subscription billing, payment forms, edge functions for MercadoPago, or webhook handlers.
Use when building Cardano transactions with MeshJS SDK. Covers MeshTxBuilder API for sending ADA, minting NFTs and tokens, spending from Plutus scripts, staking, governance voting, DRep registration, and multi-sig patterns. Includes correct method ordering, coin selection, fee calculation, and troubleshooting common Cardano transaction errors.
Use when integrating Cardano wallets with MeshJS SDK. Covers browser wallet connection (CIP-30) for Eternl, Nami, Lace, Flint, and Yoroi, headless server-side wallets from mnemonic or private keys, transaction signing, CIP-8 data signing for authentication, multi-signature workflows, and React wallet integration patterns.
Integrating TanStack DB with meta-frameworks (TanStack Start, Next.js, Remix, Nuxt, SvelteKit). Client-side only: SSR is NOT supported — routes must disable SSR. Preloading eager collections in route loaders with collection.preload(). On-demand Query Collections require preloading the live query because source collection preload is a no-op. Multiple collection preloading with Promise.all. Framework-specific loader APIs.
How to query OpenTelemetry metrics datasets in Honeycomb correctly. Metrics datasets follow different rules from trace/event datasets — many operations (bare COUNT, RATE_SUM, RATE_AVG, RATE_MAX, CONCURRENCY) are forbidden, temporal aggregation is automatic, and each metric has its own attributes. Use this skill when querying a metrics dataset (gauges, counters, histograms, sums), asking about temporal aggregation (RATE, INCREASE, SUMMARIZE, LAST), finding the metrics dataset or discovering metric names and attributes, debugging unexpected metrics query results, or querying infrastructure metrics like CPU, memory, disk I/O, or network stats. Do NOT use for instrumenting metrics (use otel-instrumentation), querying event datasets with "metrics" in their name, or conceptual questions (use observability-fundamentals).
Find and explore RevOS metrics — the measures of the org's semantic model, as the app's Metrics page lists them — through the RevOS MCP server: which metrics exist, what each one aggregates and how it's formatted, which tables, segments, and dashboard cards use it, and what its value is right now, counted over a segment or a few conditions and optionally broken down by a dimension. Use this whenever the user asks "what metrics do we have", "is there a metric for win rate / ARR / open pipeline", "where is this metric used", "what's open pipeline for the EMEA segment", "deal amount by stage", or wants a metric's value the same way a dashboard card would show it — even if they never say "metric". For putting a metric on a dashboard, use the dashboards skill; it builds on this one.
Use when working on the underlying infrastructure of BK-CI microservices, such as conditional configuration, event-driven design, inter-service communication, internationalization, and logging conventions. Prefer this when the user needs to set up multi-environment configuration, asynchronous events, Feign calls, or unified i18n/logging.
Migrates existing Xcode projects to Tuist generated workspaces with build and run validation, external dependency mapping, and migration checklists. Use when adopting Tuist for an existing app or converting a hand-edited Xcode project to generated projects.
Run a Mixture of Experts (MoE) audit on any topic, plan, codebase, evidence archive, or process. Dynamically spawns specialized subagents with different critical lenses to cross-reference findings and detect flaws, overlap, retention issues, or drift. Use when designing architectures, analyzing complex code, verifying multi-step plans, classifying evidence artifacts, or looking for duplicated intent in a repo.
Deep-dive analysis of a single MLB player (hitter or pitcher) for the Yahoo Fantasy Baseball 2K25 league. Web-searches FanGraphs (ATC projections), Baseball Savant (xwOBA/xBA/xERA), MLB.com (lineups, probables), RotoWire (weather, injuries), and RotoBaller (closer depth) to produce the full set of structured player signals defined in the signal framework. Emits form_score, matchup_score, opportunity_score, daily_quality, regression_index, obp_contribution, sb_opportunity, role_certainty for hitters and qs_probability, k_ceiling, era_whip_risk, streamability_score, two_start_bonus, save_role_certainty for pitchers. Use when you need to analyze player, compute daily_quality, compute regression index, produce player signals, run a hitter analysis, run a pitcher analysis, or prep start/sit inputs for the lineup optimizer.
Computes the full impact of a proposed MLB fantasy trade across all 10 H2H categories (R/HR/RBI/SB/OBP, K/ERA/WHIP/QS/SV), rest-of-season dollar value, positional flexibility, slot-value optionality, adverse-selection prior, and weeks 21-23 playoff impact. Produces a signed verdict (accept / counter / reject) with rationale and a specific counter if applicable. Use when user mentions "trade evaluation", "trade value", "should I accept", "trade delta", "counter offer", or pastes in a trade proposal from Yahoo. Defaults to COUNTER in the middle band — pure REJECT is reserved for clearly predatory offers.
Apply Model-First Reasoning (MFR) to code generation tasks. Use when the user requests "model-first", "MFR", "formal modeling before coding", "model then implement", or when tasks involve complex logic, state machines, constraint systems, or any implementation requiring formal correctness guarantees. Enforces strict separation between modeling and implementation phases.
Use the "demand-signal backward inference" method to find part-time or side-hustle opportunities in the AI era — don't search for "teach you to make money" posts (those are polluted sources from course sellers fishing for followers), but instead look at interest-neutral demand signals such as industry reports, hiring data and procurement data, infer opportunities an individual could supply, and cross-validate with multiple independent signals; each opportunity then goes through an anti-scam + timeliness rubric. Trigger words: "help me find opportunities" / "find AI part-time work" / "what can make money" / "money find" / "find side hustles". Prerequisite: requires .money-state.json (if absent, first route to money-init).
Status dashboard for the cheat-on-money skill. Shows the user profile, candidate opportunities and their anti-scam verdicts, currently executing opportunities and progress, review records, and suggested next steps. No side effects; can be called at any time. Trigger words: "money status" / "my current progress" / "dashboard" / "money status" / "what should I do now".
Expand an image-generation request into a detailed MOSS-Image caption or spatial layout, and compile a local JSON draft into a ready-to-paste prompt. Use for prompt enhancement, image composition and text placement; this skill does not generate images.
Huawei Ascend NPU model compression tool (msModelSlim). Use for LLM quantization (W4A8, W8A8, W8A8S, W8A16), MoE model compression, multimodal model compression (Qwen-VL, InternVL, HunyuanVideo, FLUX, SD3), calibration data preparation, precision auto-tuning, sensitive layer analysis, custom model integration, and deployment in MindIE/vLLM-Ascend. Supports Qwen, LLaMA, DeepSeek, GLM, Kimi, InternLM and more.
Using the dbt-materialize adapter to manage Materialize streaming pipelines with dbt. Covers materializations (source, source_table, view, materialized_view, sink, table, seed), profile configuration, index creation, blue/green deployments (deploy_init, deploy_promote, deploy_cleanup), cluster management, strict mode, and testing. Use this skill whenever the user asks about writing dbt models for Materialize, configuring dbt profiles for Materialize, running dbt against Materialize, blue/green or zero-downtime deployments with dbt, creating sources or sinks in dbt, troubleshooting dbt-materialize issues, or migrating existing dbt projects to Materialize. Also trigger when the user mentions dbt-materialize, materialized_view materialization, deploy_init, deploy_promote, deploy_await, strict_mode, refresh_interval, retain_history, or partition_by in a dbt context.
Wire n8n error handling so failures are loud, structured, and recoverable. Use when building any webhook/API workflow, a scheduled or unattended workflow, or any path where a silent failure would drop user-visible work — and whenever the user mentions error handling, onError, continueErrorOutput, error branches/outputs, retries, retryOnFail, Respond to Webhook status codes, 4xx/5xx, Error Trigger, or "my workflow fails silently". Covers per-node error outputs and wiring, retry/self-healing, error-trigger workflows, and 4xx/5xx response shapes.
High-speed port scanning with naabu. Use when you need port discovery or liveness detection on target hosts/networks. naabu is a fast port scanner from ProjectDiscovery supporting SYN/CONNECT/UDP scans, with performance far exceeding nmap, plus batch targets, CDN exclusion, and nmap integration. Use this skill for any scenario involving port scanning, port discovery, host liveness detection, or network probing. If naabu results are insufficient, fall back to nmap
Reference: rapid three-color triage (green/yellow/red) of inbound NDAs so team members only spend lawyer time on agreements that truly need review. For sales and BD staff, for self-screening before contacting legal. Loaded automatically when /commercial-legal:review detects an NDA.
Transforms negotiations into structured discovery using tactical empathy, interest analysis, and calibrated questions from Voss, Fisher, and Malhotra. Use when preparing for or conducting any negotiation — deals, contracts, salary, partnerships, or vendor terms.
Network flow extractor that analyzes pcap/pcapng files to identify outbound connections with automatic DNS hostname resolution. Use when you need to enumerate network destinations, identify what hosts a device communicates with, or map IP addresses to hostnames from packet captures.
Monitor, query, and manage New Relic observability data via the newrelic CLI. Covers NRQL queries and organization-scoped macros, AI Monitoring telemetry, APM performance triage, deployment markers, read-only alert and incident inspection, infrastructure monitoring, agent diagnostics, and identity/access administration. Use when user asks about LLM token usage or AI application telemetry, application performance, error rates, slow transactions, deployment tracking, incident inspection, New Relic setup, users, groups, roles, permissions, or access grants.
Web server vulnerability scanning with Nikto. Use when you need to detect known vulnerabilities, outdated software versions, dangerous files/CGI, or misconfigurations on a web server. Nikto includes 7000+ checks covering common OWASP issues. Use this skill for any scenario involving web vulnerability scanning, server security checks, or configuration auditing
Takes a list of npm package names (yours or competitors'), fetches 12 weeks of daily download data from the npm API, computes a breakout velocity score per package to identify hockey-stick growth, fetches maintainer profiles from the npm registry and GitHub API, and outputs a ranked lead brief for each breakout package with who built it, how to reach them, and what to say. Use when asked to find evangelists before they are famous, track competitor package momentum, identify breakout npm packages, map npm maintainers to Twitter or GitHub, or find DevTools leads from package growth signals. Trigger when a user says "find leads from npm packages", "who maintains these breakout packages", "track npm download trends", "find evangelists before they are famous", or "map npm maintainers to Twitter".
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.