Skills
100,928 packaged capabilities and playbooks for agents. Install any of them with one command.
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Graph and network analysis toolkit. Four graph types (directed, undirected, multi-edge), centrality, shortest paths, community detection, generators, I/O (GraphML, GML, edge list), matplotlib viz. For large graphs (100K+ nodes) use igraph or graph-tool; for GNNs use PyG.
Python toolkit for neurophysiological signal processing: ECG (HR, HRV, R-peaks), EEG (complexity, PSD), EMG (activation onset), EDA/GSR (SCR decomposition), PPG, and RSP. Includes synthetic signal simulation. Alternatives: BioSPPy (less maintained), MNE (EEG/MEG specialist), heartpy (ECG only), scipy.signal (raw DSP).
Coach the user on what to fix first — rank the audit findings into a single, ordered to-do list by score impact and effort, and explain why each item is where it is. Read-only; advises, does not change anything. Use when the user asks what to do next, what to fix first, what matters most, how to prioritize, or where to start after an audit.
Node version discipline — before running tsc / eslint / build / test / install in any Node project, align the Node version to the project's declared version (.nvmrc / .node-version / .tool-versions / volta / engines.node) and disclose it in the verification report, preventing false-pass / false-fail when the host default Node mismatches the project-pinned version; when the project declares no Node version at all, ask the user for the version and offer to persist a declaration file so future sessions/CI auto-align. Use this skill whenever the user is about to run a version-sensitive Node command, or mentions Node version mismatch / wrong Node / version conflict. 中文触发词「node 版本对齐」「nvm 对齐」「.nvmrc」「Node 版本纪律」「对齐 Node 版本」「切换 node 版本」「版本不匹配」「初始化 node 版本管理」「为工程增加 node 版本声明」「给工程加 .nvmrc」「无 .nvmrc 时补一个」「工程没有 node 版本管理」, English aliases node version discipline, nvm use, align node version, switch node version, add nvmrc, initialize node version.
Use oil-ppt to create, modify, continue, check, and build 16:9 HTML presentations, and export hybrid editable PPTX as needed. Pairs with oil-tone by default to handle audience-facing copy, with each page as standalone HTML. Use when the user asks to create a presentation, refine page by page, batch-review, or deliver an offline presentation. Not for scrolling web pages, ordinary articles, or a single poster, and it does not treat any existing PPTX as a losslessly importable source project.
When the user wants to optimize post-signup onboarding, user activation, first-run experience, or time-to-value. Also use when the user mentions "onboarding flow," "activation rate," "user activation," "first-run experience," "empty states," "onboarding checklist," "aha moment," or "new user experience." For signup/registration optimization, see signup-flow-cro. For ongoing email sequences, see email-sequence.
Fetch dependency source code to give AI agents deeper implementation context. Use when the agent needs to understand how a library works internally, read source code for a package, fetch implementation details for a dependency, or explore how an npm/PyPI/crates.io package is built. Triggers include "fetch source for", "read the source of", "how does X work internally", "get the implementation of", "opensrc path", or any task requiring access to dependency source code beyond types and docs.
Write OpenTofu modules and tests for homelab infrastructure (infrastructure/modules/). Use when: creating new modules, writing or modifying .tftest.hcl test files, adding variables/outputs/resources, debugging test failures, or questions about tftest syntax. Triggers: "opentofu module", "terraform module", "tofu module", "create module", ".tftest.hcl", "tftest", "test my module", "module test", "infrastructure test", "variables.tf", "outputs.tf", "module testing", "assertion", "task tg:test", "test-config"
Bypasses anti-bot protections using Oxylabs Web Unblocker, an AI-powered proxy that handles fingerprinting, JavaScript rendering, and retries automatically. Use when the user needs to scrape protected websites, bypass CAPTCHAs, access blocked content, or when regular proxies fail due to anti-bot measures.
Medical/scientific paper writing workflow skill. Manages the full pipeline from literature search to submission-ready manuscript. Creates and manages a project directory with IMRAD-format section files, literature matrix, reference management, and quality checklists. Supports both English and Japanese papers. Triggers: 'write paper', 'paper-write', 'start manuscript', '論文を書く', '論文執筆', '論文プロジェクト', 'manuscript', 'research paper', '原稿作成'.
Full-featured computational pathology toolkit. Use for advanced WSI analysis including multiplexed immunofluorescence (CODEX, Vectra), nucleus segmentation, tissue graph construction, and ML model training on pathology data. Supports 160+ slide formats. For simple tile extraction from H&E slides, histolab may be simpler.
Run pathway and gene-set enrichment analysis on gene lists or ranked gene data, then interpret the results. Use whenever the user has a set of genes (differentially expressed genes from PyDESeq2/Scanpy, CRISPR-screen hits, cluster marker genes, proteomics hits) and wants to know which biological pathways, GO terms, or gene sets are over-represented or enriched. Covers over-representation analysis (ORA / Enrichr / Fisher / hypergeometric), ranked Gene Set Enrichment Analysis (GSEA / preranked), single-sample scoring (ssGSEA/GSVA), and functional profiling via gseapy, g:Profiler, Enrichr libraries, MSigDB, GO, KEGG, Reactome, and WikiPathways — plus gene-ID mapping, choosing the right background universe, multiple-testing correction, redundancy reduction, dotplots/enrichment maps, and publication-ready tables. Use this for "pathway analysis", "enrichment analysis", "GO enrichment", "KEGG/Reactome pathways", "GSEA", "over-representation", "functional annotation", or "what pathways are my genes in".
Hardware-agnostic quantum ML framework with automatic differentiation. Use when training quantum circuits via gradients, building hybrid quantum-classical models, or needing device portability across IBM/Google/Rigetti/IonQ. Best for variational algorithms (VQE, QAOA), quantum neural networks, and integration with PyTorch/JAX/TensorFlow. For hardware-specific optimizations use qiskit (IBM) or cirq (Google); for open quantum systems use qutip.
Design and build cohesive web pages with custom visual identity — landing pages and portfolios get rich anatomy + section archetypes; any other page type (blog, about, pricing, contact, coming-soon, dashboard, admin, e-commerce, custom) is supported through generic anatomy + skeleton. Use this skill whenever the user mentions: landing page, portfolio, personal site, hero section, marketing page, product page, sales page, splash page, blog page, about page, pricing page, contact page, coming-soon, waitlist, dashboard, admin panel, e-commerce store, redesign my site, design my portfolio, build a portfolio, work showcase, hire-me page, perfect-ui, perfect landing, or asks to create any web page surface. Two tiers: special (landing | portfolio — rich treatment) and generic (everything else — universal craft toolkit). Self-contained 8-phase pipeline: vibe discovery → visual direction (color/typography/mood) → custom icon set (NO emoji, NO icon library) → AI-generated visuals → optional shader effects layer → inline plan + implement on Next.js + Tailwind + shadcn. Always proposes effect layer as optional. No refusals; outputs distinctive sites, not AI slop.
Audits container and pod configuration for escape-enabling misconfiguration using the Kubernetes Python client - privileged flags, dangerous capability grants, host path mounts, shared namespaces, and CVE-2022-0492 style cgroup abuse. Use when sweeping a cluster for workloads that could break out, producing a posture report, or checking configuration before enforcement is switched on. Keywords: privileged, hostPath, hostPID, capabilities, CVE-2022-0492, cgroup, kubernetes python client, posture audit. Do not use for runtime syscall-based detection - use detecting-container-escape-attempts.
Deploy Zeek (formerly Bro) as a passive network security monitor to generate structured logs of protocol metadata (HTTP, DNS, TLS, SSH, SMTP, FTP, and more), write custom detection scripts, and integrate outputs with SIEM platforms. Use when standing up continuous, high-fidelity network traffic monitoring for threat detection, anomaly identification, or forensic investigation beyond what raw PCAP analysis provides.
Build and analyze phylogenetic trees using MAFFT (multiple alignment), IQ-TREE 2 (maximum likelihood), and FastTree (fast NJ/ML). Visualize with ETE3 or FigTree. For evolutionary analysis, microbial genomics, viral phylodynamics, protein family analysis, and molecular clock studies.
Auto-annotate plasmids with features (promoters, terminators, resistance, origins, tags, fluorescent proteins) via BLAST against curated DBs (Addgene, fpbase, SnapGene). FASTA or raw sequence in; annotated GenBank, interactive HTML maps, CSV tables out. Handles circular topology. Use to verify synthetic constructs, prep Addgene submissions, share maps, or batch-annotate cloning libraries.
Find metadata that already exists in a Salesforce org by meaning, when you do not know its exact API name. Use to find objects, fields, flows, Apex classes, picklist values, permission sets, validation rules, record types, and sharing rules by what they store or do. Use before creating metadata to check whether something similar already exists, and before writing Apex, LWC, SOQL, or Flow logic to confirm the real names. Use to read how a field, object, or validation rule is configured, and which profiles and permission sets can read or edit a field. Works through the Metadata Grounding MCP (search_metadata, query_metadata, describe_metadata) or the Salesforce MCP operations searchMetadata, queryMetadata, and describeMetadata. Needs Salesforce Catalog in the org. DO NOT TRIGGER for choosing between grounding, SOQL, and the CLI (use platform-metadata-discovery-get), retrieving source (platform-metadata-retrieve), or Data Cloud DLO and DMO schema (data360-code-extension-generate).
Clone live web pages into a local Next.js + Tailwind CSS project for rapid prototyping. Use this skill whenever a user shares a URL or screenshot and wants to replicate, redesign, or iterate on that page locally — whether they say "clone this site", "make a prototype based on this page", "recreate this UI", "build something that looks like this", or simply paste a link and ask you to turn it into code. Also trigger when the user wants to add new pages, modify existing pages, or extend a prototype project that was previously created by this skill. Even if the user just says "I want to build a page like X" with a reference link or image, this skill applies.
POLAR v5.0.0 — ETH alpha hunter, senpi_runtime_helpers migration. Plumbing-only flip from openclaw-CLI subprocess + mcporter subprocess to in-process SenpiClient (direct HTTPS for MCP, direct HTTP POST to runtime /signals, long-lived producer_daemon). Thesis preserved verbatim from v4.2.0: ETH single-asset hybrid, hyperfeed SM gates (pct≥5%, traders≥30, cc_15m≥0.3), structural gates (4h trend, 1h-4h alignment, 15m momentum, RSI), multi-factor scoring (~17 max), conviction-tiered leverage (5x standard / 7x conviction / 10x apex), MIN_SCORE 12, FP-001 quiet hours (00-04 UTC unless apex score 17+).
Fast in-memory DataFrame library for datasets that fit in RAM. Use when pandas is too slow but data still fits in memory. Lazy evaluation, parallel execution, Apache Arrow backend. Best for 1-100GB datasets, ETL pipelines, faster pandas replacement. For larger-than-RAM data use dask or vaex.
Perform a final quality pass fixing alignment, spacing, consistency, and micro-detail issues before shipping. Use when the work is functionally complete and needs finishing touches—not when the hierarchy, structure, tone, or technical foundation still need major changes.
Use this skill whenever an LLM agent needs to search, browse, or download 3D models from Poly Pizza (poly.pizza) using their REST API. Triggers on any task involving: finding free low-poly 3D models, searching the Poly Pizza catalogue, fetching model metadata or download URLs, retrieving popular models, or downloading .glb files from Poly Pizza. Use this skill proactively whenever the agent needs to obtain 3D assets programmatically, even if the user just says "find me a 3D model of X" without mentioning Poly Pizza by name.
Order Seattle's favorite pizza from the terminal — every endpoint, plus discount stacking, slice rotation across stores, half-and-half pies, and a small-party planner nobody else has. Trigger phrases: `order from pagliacci`, `what pagliacci slices are available`, `plan a pagliacci order for the family`, `build a half-and-half pagliacci pizza`, `pagliacci rewards balance`, `use pagliacci`, `run pagliacci`.
Every Trend Hunter feature, plus a local SQLite corpus, FTS5 search, FAQ Q&A extraction, and agent-native JSON no... Trigger phrases: `what's trending on trendhunter`, `search trendhunter for`, `weekly trend digest`, `trend hunter FAQ for`, `rising keywords on trendhunter`, `active trend hunters this month`, `use trendhunter`, `run trendhunter-pp-cli`.
Compares code formatting and formatting IR between Biome and Prettier to ensure that Biome's formatting is consistent and correct. Use when validating formatter changes, debugging formatting differences, or comparing output for JavaScript, TypeScript, CSS, or other languages.
World-class prompt powerhouse that generates production-ready mega-prompts for any role, industry, and task through intelligent 7-question flow, 69 comprehensive presets across 15 professional domains (technical, business, creative, legal, finance, HR, design, customer, executive, manufacturing, R&D, regulatory, specialized-technical, research, creative-media), multiple output formats (XML/Claude/ChatGPT/Gemini), quality validation gates, and contextual best practices from OpenAI/Anthropic/Google. Supports both core and advanced modes with testing scenarios and prompt variations.
Facilitate methodical review of proposals (technical designs, product specs, feature requests). Use when asked to "review this proposal", "give feedback on this doc", "help me review this RFC", or when presented with a document that needs structured feedback. Handles markdown files, GitHub gists/issues/PRs, and other text formats. Chunks proposals intelligently, predicts reviewer reactions, and produces feedback adapted to the proposal's format.
Reads, validates, and exports protocols.io data using the documented REST v3/v4 endpoints and the official MCP endpoint, and builds non-executing mutation plans. The bundled client makes bounded GET requests to official hosts only with --execute, and also validates saved protocol JSON offline for step order, version, DOI, and attribution metadata. Use when fetching a protocol, its steps, materials, or PDF from protocols.io by exact version. Use when validating a saved protocol snapshot for provenance before reuse. Use when planning a protocol create, update, publish, upload, or organization export without running it. Use when checking protocols.io rate limits, pagination, or authentication. Do not use for other protocol repositories or general literature search.
Integration with protocols.io API for managing scientific protocols. Use this skill when working with protocols.io to search, create, update, or publish protocols; manage protocol steps and materials; handle discussions and comments; organize workspaces; upload and manage files; or integrate protocols.io functionality into workflows. Applicable for protocol discovery, collaborative protocol development, experiment tracking, lab protocol management, and scientific documentation.
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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.