Skills
97,222 packaged capabilities and playbooks for agents. Install any of them with one command.
All
Deploy and configure OpenClaw AI gateway on KASM workspaces or standalone Docker. Multi-provider LLM routing (Anthropic, OpenAI, Gemini, Groq, Bedrock) with multi-channel messaging (WhatsApp, Telegram, Discord, Slack). Covers Docker deployment, security hardening, persistent storage, browser sidecar, and webhook automation. Use when: deploying OpenClaw, configuring AI gateway channels, setting up openclaw container on KASM, troubleshooting "token mismatch" or "EACCES" errors, or securing gateway binding.
Operate Orca-managed worktrees, folder contexts, terminals, repos, automations, artifacts, skill sharing, worktree comments, and Orca's embedded browser through the `orca` CLI. Use when the user says "$orca-cli", "Orca worktree", "child worktree", "spawn codex/claude in a worktree", "read/wait/send Orca terminal", "handoff" / "handover" / "give this to another agent", "Orca browser", "orca artifacts", or "share skills". Prefer it over raw git worktree, ad hoc PTYs, or Computer Use when Orca state is involved. Use Computer Use only when a visible window needs GUI control that a CLI, filesystem, or API cannot do.
Analyze local Q&A session JSONL files and produce a complete, auditable English Markdown weekly report over consecutive time windows, with all data required for downstream Feishu document and whiteboard rendering. Use for requests such as "analyze the latest week of sessions," "generate a community Q&A weekly report," or "compare with last week." This skill does not ingest other message sources or create/upload online documents.
Perform evidence-driven security code reviews across application repositories, services, libraries, and pull requests. Use when Codex needs to audit source code for security flaws, map trust boundaries, verify authentication or authorization, trace untrusted data to sensitive sinks, assess business logic or cryptography, or produce prioritized findings when no narrower language or platform review skill fits.
Build a new individual page inside an existing product or application. Use for page types such as home, product, feature, landing, pricing, tool, documentation, campaign, article, dashboard, settings, and error pages when the task includes page purpose, structure, content, components, implementation, and verification. Do not use for whole-site information architecture, site-wide navigation planning, or isolated component construction.
Expert pandas skill for data manipulation, cleaning, analysis, and transformation. Use this skill when working with tabular data, CSV/Excel files, data analysis tasks, or any data processing workflow that involves pandas DataFrames. Provides executable scripts for common operations and comprehensive reference documentation.
Use when the user gives a journal or magazine name and wants to know submission requirements, submission format/style checklists, official journal website information, community reviews, review speed, fees, article types, format details, or asks "how do I submit to this journal / is it reputable / research the submission guide". Verifies the official journal website and community reviews online, and by default isolates all intermediate files to `.bensz-api/task-{yyyymmdd-hhmm}-{short-description}/paper-know-journal/` in the current working directory, delivering only `KnowJournal-{journal-name}.md` at the end. ⚠️ Not applicable: when the user wants to select a journal for a manuscript (use paper-select-journal), write the paper body, download full-text PDFs, or just ask a simple fact that needs no finished document.
Design and audit partner risk due diligence for integrations, resellers, agencies, affiliates, marketplace partners, creators, data-sharing partners, AI providers, and co-marketing. Covers strategic fit, security/privacy, legal, operational dependency, brand risk, support burden, incentives, exit plans, and monitoring. Use when committing to partner ecosystems or joint go-to-market.
End-to-end password spray playbook. User enumeration, lockout detection, password pattern generation, spray execution across all protocols, error code differentials, and engagement discipline. Unifies M365/Entra, Okta, Exchange, Kerberos, SharePoint, XMLRPC, OIDC, and AD SMB/WinRM spraying into one methodology.
(forwward) Creates high-conversion landing pages, emails, and social posts using the Dual-PCP (Perception-Context-Permission) framework that resonates rather than directs. Triggers on landing pages, conversion copy, email sequences, ICP targeting, copy audits, perception shifting, micro-compliance, or SEO persuasive writing.
Use this skill when you need to design JMeter test plans with Thread Groups, samplers, data sets, assertions, timers, CLI runs, and HTML reports; triggers include JMeter performance testing, performance testing, and performance-test-jmeter.
Maintain a personal CRM — track relationships, last-touch dates, follow-ups owed, context from past conversations, and who deserves a check-in. Use this whenever the user says 'who do I owe a follow-up to,' 'when did I last talk to,' 'personal CRM,' 'track this contact,' 'log this conversation,' 'who should I check in with,' 'add [name] to my contacts,' or asks about their relationships and follow-up history. The skill maintains a structured `contacts/` folder with one markdown file per person, automatically surfaces follow-ups, and pulls context before any meeting.
Generate rich personality profiles from social media data exports (Twitter/X, LinkedIn, Instagram). Use when a user wants to analyze their social media presence, create a personality profile for AI personalization, understand their communication patterns, or extract insights from their digital footprint. Triggers on requests like "analyze my Twitter data", "create a personality profile", "what can you learn about me from my posts", "personalize an AI for me", or when users provide social media export files.
Run the PAIDF Orchestration Event Video Generation DAG on Kubernetes - image-to-video anomaly generation, auto-labeling, and anomaly dataset generation. Select for requests about event video generation, anomaly video generation, image-to-video synthesis, Cosmos3 image2video, anomaly dataset creation, safety/surveillance SDG, or generating person-falling, person-climbing, person-running, fighting, smoking/vaping, fire/smoke, or shoplifting video clips from a seed image. Runs environment setup first when controller readiness is unknown. Not for person-crop clothing/attribute augmentation (that is image-attribute-augmentation-workflow) and not for video style transfer.
Official NVIDIA-authored guidance for navigating PhysicsNeMo — pick the model, datapipe, or example for a SciML/AI4Science task (surrogates, forecasting, downscaling, physics-informed, inverse, generative). Points at existing files via live repo search; never writes code. Do NOT use for installation or environment setup, training-loop or other code authoring/scaffolding, contributor/CI/packaging questions, repo-specific questions in physicsnemo-sym/-cfd/-curator, or general (non-physics) ML/PyTorch.
Provide CI/CD best practices and pipeline templates for GitHub Actions and GitLab CI, recommending configurations based on project type (frontend, backend, fullstack, library, monorepo, mobile). Trigger when users ask about setting up CI/CD, automating builds, improving pipelines, or mention keywords like GitHub Actions, GitLab CI, pipeline templates, or deployment automation.
Use when developing BK-CI pipeline plugins, such as adding an Atom, writing `task.json`, defining inputs and outputs, handling multilingual runtimes, and debugging and publishing plugins. Prefer this when the user needs to work on the plugin itself rather than the executor or pipeline model.
Pharmacokinetic and pharmacodynamic modelling and simulation - non-compartmental analysis, compartmental and population PK, PK/PD and exposure-response, TMDD, PBPK orientation, bioequivalence, allometric scaling and first-in-human dose, drug interaction prediction, and Bayesian therapeutic drug monitoring. Use when analysing concentration-time data, deriving exposure metrics, fitting PK or PD models, or evaluating dosing regimens. Triggers include "pharmacokinetics", "pharmacodynamics", "PK/PD", "NCA", "non-compartmental", "AUC", "Cmax", "lambda z", "half-life", "clearance", "volume of distribution", "compartmental model", "population PK", "popPK", "NONMEM", "nlmixr2", "Pharmpy", "Monolix", "exposure-response", "Emax", "EC50", "indirect response", "effect compartment", "TMDD", "PBPK", "bioequivalence", "RSABE", "ABEL", "allometric scaling", "first-in-human", "MABEL", "drug-drug interaction", "DDI", "ICH M12", "concentration-QTc", "therapeutic drug monitoring", "MIPD", and "dosing regimen".
Implements Manus-style file-based planning for complex tasks. Creates task_plan.md, findings.md, and progress.md. Use when starting complex multi-step tasks, research projects, or any task requiring >5 tool calls. Now with automatic session recovery after /clear.
Analyzes platform business models by distinguishing Aggregators from Platforms, mapping network effects, and identifying when to externalize internal primitives as ecosystem growth engines. Use when evaluating platform dynamics, designing marketplace strategy, or analyzing aggregation and network effects.
Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.
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.