Skills
101,174 packaged capabilities and playbooks for agents. Install any of them with one command.
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Land community pull requests as the contributor and answer community issues on thedotmack/claude-mem. Takes stock of every open PR (the owner's own included, except the ones the owner marked experimental) and community issue, triages each against the owner's merge philosophy and the cmem.ai hosted-service boundary, finishes somewhat-aligned PRs on the contributor's own branch, squash-merges so the contributor stays the commit author on main, thanks them by name, closes fixed issues with credit to reporter and fixer, keeps the private ledger and contributor roster current, and reports what it decided. Use when asked to "go through the PRs", "merge contributor PRs", "help contributors with their PRs", "land the new community PRs", "triage new issues and PRs", "run the community sweep", "keep the momentum", or "grow the community".
Production UI component code in React/TypeScript, SwiftUI, and modern CSS with full state matrices, ARIA attributes, keyboard handling, and design token consumption. Use when building or reviewing a button, modal, form, input, table, or any component that needs all of its states covered.
[AUTO-INVOKE] MUST be invoked BEFORE deploying DeFi contracts (DEX, lending, staking, LP, token). Covers anti-whale, anti-MEV, flash loan protection, launch checklists, and emergency response. Trigger: any deployment or security review of DeFi-related contracts.
Recall and troubleshoot Arthur's documented Dell U3225QE multi-computer hub, KVM, DisplayLink, audio, and peripheral topology. Use for Arthur's setup or when someone explicitly asks about this published workstation; do not assume the same wiring for other Dell desks.
Look up the latest stable version of any open-source package across npm, PyPI, Go, Cargo, Maven, and NuGet. Use when the user asks 'what's the latest version of X', 'what version should I use', 'is X deprecated', 'how outdated is my package.json/requirements.txt/Cargo.toml', or needs version numbers for adding or updating dependencies. Also covers pinning versions, checking if packages are maintained, or comparing installed vs latest versions. Do NOT use for private/internal packages or for looking up documentation (use context7).
Use this skill for hands-on DOCA Arg Parser CLI work on a shipped sample or new DOCA-using app: adding, removing, or renaming flags; wiring `doca_argp_init` → register params → `doca_argp_start` → `doca_argp_destroy` in order; choosing a parameter type from the full public enum (`DOCA_ARGP_TYPE_STRING`, `_INT`, `_BOOLEAN`, `_DEVICE`, `_DEVICE_REP`, `_DOUBLE`—six values, not three); preserving the built-in DOCA flags (`-h` `-v` `-l` `--sdk-log-level` `--log-filter` `-j`/`--json`, NOT `--json-config`); `--device` is per-program; or debugging `DOCA_ERROR_BAD_STATE` / `INVALID_VALUE` / `NOT_SUPPORTED` / `IO_FAILED` from `doca_argp_*`. Trigger on implicit phrasings: “add a custom flag to a DOCA sample,” “should I use getopt here,” “BAD_STATE registering a new param,” “my JSON config key is rejected,” or “my sample's --json is ignored.” Refuse and route elsewhere for variadic-flag / subcommand / shell-completion features, DOCA Core context, or DOCA Log internals.
DOCA Flow packet steering on NVIDIA NICs/DPUs, linked into a C application: match/action pipes, ports, representors, forwarding, hairpin, and counters. Trigger on packet steering, classifier, rule-matching, representor, hairpin, or 5-tuple-to-queue questions even when “DOCA Flow” is not named. Also covers pipe validation before hardware programming, Flow/DOCA version matching, and Flow API errors. First app: follow the local bundle (doca-setup, doca-programming-guide, doca-flow, doca-public-knowledge-map). Stage 1: pull nvcr.io/nvidia/doca/doca (NGC catalog tag, never invent); Stage 2 needs a real NIC. Then ls samples inside the container; never emit main.c, a Dockerfile, or hand-typed -l flags. Route software-only host pipelines, plain DPDK `rte_flow`, kernel TC, OVS, BFB bring-up, and DPU OS installation elsewhere. DPU OS installation is destructive and always requires explicit confirmation.
Use this skill when the user is writing their first DOCA app or asking a library-agnostic programming question — picking a shipped sample to copy and modify, wiring pkg-config + meson (or FFI from Rust / Go / Python against the public C ABI), walking the Core lifecycle (create → configure → start → connect → use → stop → destroy), or decoding a DOCA_ERROR_*. Trigger on implicit phrasing: “write my first DOCA program”, “meson line for doca_rdma_*”, “DOCA_ERROR_BAD_STATE on first call”, “call DOCA from Rust”, “built clean but nothing on the wire”. Refuse install / hugepages / pkg-config (doca-setup), docs or version lookup (doca-public-knowledge-map), and library-internal API work (matching library skill)
Dual Stacking enrollment operations on Stacks — earn BTC-denominated rewards (paid in sBTC) by holding sBTC. Check enrollment status and APR data, enroll with a single contract call (no lockup, minimum 10,000 sats sBTC), opt out, and query earned rewards by cycle. Write operations require an unlocked wallet.
Design experiments and studies BEFORE data is collected — choosing a design, randomizing, blocking, and laying out treatment combinations so results are interpretable. Use whenever someone is planning a study, asks how to assign subjects/samples to groups, mentions randomization, blocking, stratification, controls, factorial or fractional-factorial designs, design of experiments (DOE), screening many factors, response-surface optimization, crossover or repeated-measures or split-plot designs, cluster/group randomization, Latin squares, plate layouts, batch/run-order effects, replication vs. pseudoreplication, or sequential/adaptive/group-sequential designs. Trigger even for informal phrasings like "how should I set up this experiment", "how do I avoid confounding", "what's the best way to test these 6 factors", or "assign these mice to conditions". For computing the sample size or power once the design is chosen, use statistical-power; for analyzing data already collected, use statistical-analysis.
Query Feishu attendance data (user-task / user-stats). user-task checks clock-in tasks/shifts; user-stats checks attendance statistics (attendance/late arrivals/early departures/leave). Note: Only Tenant Token is supported; SDK v3.5.3 does not accept User Token. Each query is limited to 31 days; longer ranges are rejected. Use when the user asks to “check attendance,” “check clock-in records,” “attendance statistics,” or “attendance details.”
Query Feishu OKRs and report progress. `okr cycle list` lists tenant-level OKR cycles; `okr progress list/create` queries or creates progress records. Note: The API requires the `source_url` field; the default placeholder `https://www.feishu.cn/okr/progress` can be changed. Uses SDK Okr.ProgressRecord + direct HTTP calls to v1/periods (v2/cycles does not exist). Use when the user asks to “check OKR cycles,” “report OKR progress,” or “update OKRs.”
Feishu visual content: whiteboards (architecture and flow diagrams; converting SVG/Mermaid/PlantUML into editable nodes; retrieving Mermaid source; cloning, quality checks and export), Feishu Slides presentations (create from XML, add/delete/edit pages, screenshots), dynamic Miaobi HTMLBox components in documents (ECharts, maps, 3D, animation, interactive dashboards), publishing Miaoda HTML apps and setting access scope, plus data chart formats and color guidelines. Use when the user wants to draw in Feishu, create slides/PPT, embed animated or interactive charts, or publish an HTML app. Not for: producing only local SVG/PPTX/HTML files; message cards (feishu-cli-messaging); HTML email (feishu-cli-mail); charts imported with Markdown (feishu-cli-docs); Bitable dashboards (feishu-cli-data)
When the user wants to create, schedule, or optimize Google Business Profile posts. Also use when the user mentions "GBP posts," "Google posts," "GMB updates," "business profile posts," "what should I post on Google," or "GBP content calendar." For overall GBP optimization, see gbp-optimization.
Professional UI/UX design expertise for full-stack applications. Covers design thinking, user psychology (Hick's/Fitts's/Jakob's Law), visual hierarchy, interaction patterns, accessibility, performance-driven design, and design critique. Use when designing features, improving UX, solving user problems, or conducting design reviews.
Manage GitLab CLI authentication including login/logout, check auth status, switch accounts, and configure Docker registry access. Use when setting up glab for first time, troubleshooting auth issues, switching GitLab instances/accounts, or configuring Docker to pull from GitLab registry. Triggers on auth, login, logout, authentication, credentials, token, Docker registry.
Design interfaces following Google's Material Design system, the unified visual language bridging digital and physical worlds. Emphasizes bold graphic design, intentional motion, adaptive layouts, and the material metaphor. Use when building modern, accessible, delightful user interfaces across platforms.
Control Home Assistant devices and automations via REST API. 25 entity domains including lights, climate, locks, presence, weather, calendars, notifications, scripts, and more. Use when the user asks about their smart home, devices, or automations
Use when the user wants text to sound more human, says writing sounds "too AI" or "too ChatGPT," asks to humanize or rewrite a draft to feel natural, or shares content wanting it to feel authentic and less robotic. Also applies to LinkedIn posts, blog drafts, or emails where the user wants a more genuine voice.
Provider-independent production workflow for AI agents assembling generated or source media into HyperFrames HTML/CSS/JS videos. Use for HyperFrames composition planning, scene architecture, media custody, animation/timing, captions/audio, deterministic preview/render QA, accessibility/flashing checks, provenance ledgers, and delivery handoff.
Check and compare software component versions on SageMaker HyperPod cluster nodes: NVIDIA drivers, CUDA toolkit, cuDNN, NCCL, EFA, AWS OFI NCCL, GDRCopy, MPI, Neuron SDK (Trainium/Inferentia), Python, and PyTorch. Use when checking component versions, verifying CUDA/driver compatibility, detecting version mismatches across nodes, planning upgrades, documenting cluster configuration, or troubleshooting version-related issues on HyperPod. Triggers on requests about versions, compatibility, component checks, or upgrade planning for HyperPod clusters.
Compose, verify, and send concise ImmoScout24 landlord contact messages when the user is already logged in on ImmoScout24 and wants to contact one or more rental listings. Use for German rental listing outreach, landlord/broker message templates, profile-based apartment introductions, and troubleshooting ImmoScout24 contact form automation. Do not use for full portal applications with PDF uploads; use a separate apartment application workflow for that.
Automatically organizes invoices and receipts for tax preparation by reading messy files, extracting key information, renaming them consistently, and sorting them into logical folders. Turns hours of manual bookkeeping into minutes of automated organization.
A decomposition playbook and anti-temptation rules for an orchestrator profile routing work through Kanban. The “don't do the work yourself” rule and the basic lifecycle are automatically injected into every Kanban worker's system prompt; this skill is the deeper playbook for when you're specifically playing the orchestrator role.
Give cited public Splunk knowledge-object governance guidance and assess user-authorized inventory, ownership, orphan, ACL, naming, lifecycle, lookup, and search-head-cluster comparison evidence without changing a deployment. Use for shared lookups, sourcetypes, saved searches, macros, field extractions, aliases, props/transforms, CIM mappings, dashboards, reports, and related objects when an administrator needs a read-only hygiene report, safe review plan, or boundary route.
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.