Skills
99,951 packaged capabilities and playbooks for agents. Install any of them with one command.
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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.
Run a sustained, multi-agent vulnerability-discovery campaign against a target: split its attack surface into slices, have builder agents hunt each slice, and have a separate critic with fresh context adversarially refute every candidate against the real artifact (a reproduced crash, a working request, a proven bypass) before it counts as a finding. Use when tasked with finding previously unknown bugs across a whole codebase, a binary, or a named live target; when you want to fan out many agents and loop until findings are proven rather than plausible; or when a single audit pass has stalled and you need builder/critic separation so the hunter never grades its own work. Dispatches auditing-code-for-vulnerabilities, analyzing-binaries, and testing-web-applications as per-slice hunters and hands proven findings to reporting-security-findings
Dispatcher for the creative suite: diagnoses a multi-asset creative request with a few questions, then routes it through the right sequence of creative skills, naming the artifact each step passes to the next, and wires in the FAL.ai automation (single model fal-ai/nano-banana-pro via docs/creative_cli.py) when available. Use when the user asks for several creative deliverables at once or an outcome that implies them — 'assets for my product launch', 'set up my brand visuals', 'I need a logo, product shots, and social posts', 'a week of content', 'rebrand everything' — or when it's unclear which creative skill applies. Produces a Creative Production Plan: chosen route, ordered skill sequence with hand-off artifacts, generation checklist, and asset output map. For a single obvious asset, skip this and use the specific skill directly.
Use this skill when the user asks MoviePilot to identify and organize a local or downloaded video/music file, season folder, recording, album directory, or mixed folder that automatic transfer did not handle. If failed transfer history IDs are supplied, use transfer-failed-retry instead.
OWASP security guidelines and Top 10 vulnerabilities USE WHEN: user mentions "OWASP", "security audit", "vulnerability scan", asks about "injection", "XSS", "CSRF", "access control", "authentication security" DO NOT USE FOR: OWASP Top 10:2025 specific - use `owasp-top-10` instead
PancakeSwap V3 CLMM farming plugin. Stake V3 LP NFTs into MasterChefV3 to earn CAKE rewards, harvest CAKE, collect swap fees, and view positions across BSC, Ethereum, Base, and Arbitrum. Trigger phrases: stake LP NFT, farm CAKE, harvest CAKE rewards, collect fees, unfarm position, PancakeSwap farming, view positions.
Use when contributing code to an existing project - guarantees that every new line mirrors the established conventions, naming schemes, architectural layering, directory layout, and stylistic choices already present in the codebase rather than drifting toward generic AI defaults
Use this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting/decrypting PDFs, extracting images, and OCR on scanned PDFs to make them searchable. If the user mentions a .pdf file or asks to produce one, use this skill.
Create and edit Pencil (.pen) design files programmatically. Generate UI designs as JSON-based .pen files with themes, variables, components, and layouts. Includes CLI tools for reading, searching, editing, and validating .pen files without requiring the Pencil desktop app. Requires Node.js 18+. Schema version 2.8.
Identifies and fixes Rails performance issues including N+1 queries, slow queries, and memory problems. Use when optimizing queries, fixing N+1 issues, improving response times, or when user mentions performance, slow, optimization, or Bullet gem. WHEN NOT: Caching-specific patterns (use caching-strategies), adding new features, or general code quality improvements unrelated to speed.
Guide performance profiling for Apple platform apps with Instruments, Xcode diagnostics, and MetricKit. Use when investigating app hangs, stutters, high CPU, memory leaks, memory growth, OOM crashes, slow launch, battery drain, thermal issues, App Store performance readiness, or when adding os_signpost and measurement hooks
Builds comprehensive forensic super-timelines using Plaso (log2timeline and psort) to correlate events across file system metadata, event logs, browser history, and registry artifacts into a unified chronological view. Use during complex forensic investigations that need cross-source event correlation, or when standard log analysis is insufficient to establish the sequence of activities for reporting findings.
Official PGYER (蒲公英) skill for app beta distribution. Use whenever the user mentions PGYER / 蒲公英 / pgyer.com, or asks to upload an ipa/apk/hap for beta testing, fetch install links or QR codes, query a beta app's version history or install counts, manage tester groups, or wire up CI/CD that publishes to PGYER. Covers iOS, Android, and HarmonyOS app distribution. Reads credentials from $PGYER_API_KEY or ~/.pgyer/config.
Use when assigning Arduino, ESP32, ESP32-S3, Pico, or Pico W pins; creating a GPIO map; assigning buttons, LEDs, sensors, buses, or actuators; migrating a pin map; or generating constexpr int declarations. Check the exact board and physical pin constraints before emitting the user's ordered raw declaration format.
Transforms workflow to use Manus-style persistent markdown files for planning, progress tracking, and knowledge storage. Use when starting complex tasks, multi-step projects, research tasks, or when the user mentions planning, organizing work, tracking progress, or wants structured output.
Use when: you need to continuously monitor competitor activity, set up competitor intelligence alerts, regularly produce monthly competitor monitoring reports, or track competitor changes in version/pricing/features/sentiment/funding. Do not use when: you only need a one-off competitor study (use pm-market / pm-search --type=competitor); the product has no clear competitors yet.
Use when: you need to improve a product's visibility and recommendation rate in AI search/generative engines (ChatGPT, Perplexity, AI Overviews, 豆包, 文心), or create a GEO (Generative Engine Optimization) plan. Do not use when: you only do traditional SEO/keyword rankings, or the product is not yet launched and has no public information to optimize.
Use when: you need to design user interview/user research plans, write interview outlines, plan samples and recruitment, or define interview execution and analysis methods. Do not use when: you only do desk research on requirements (use pm-demand); a clear conclusion already exists and you only need to validate a single assumption without interviews.
Use when: reviewing the quality of requirement documents such as PRD/BRD/MRD, checking completeness/clarity/feasibility/metrics/risks/consistency, and gatekeeping documents before development. Do NOT use when: the document does not exist yet (generate it with /pm-docs first); or only a verbal discussion is needed with no written review
Run one tick of the sales business-pod (ADR-164 §4.1, Phase 2). Loads templates/sales.json, validates it against the pod-schema, resolves agents against ruflo's agent registry, reserves budget via the Phase-2 file-based stub ledger (atomic SQLite tracker is Phase 3 per ADR-164.1), constructs per-agent dry-run prompts, posts a summary envelope to room "sales" via the federation_bbs_publish JSONL backing store, and emits a structured {podName, tickId, agentsRan, totalUsd, envelopeId, status} line for /loop ingestion. Dry-run by default; --live is reserved for Phase 3.
Blazingly fast DataFrame library written in Rust. Features a multi-threaded query engine, lazy evaluation, and efficient memory usage via Apache Arrow. Designed for high-performance data processing on a single machine. Use for large datasets (1GB-100GB+), fast data transformations, Parquet/CSV processing, complex query pipelines, memory-efficient operations, and when speed is critical (10-100x faster than pandas).
Auto-document Power BI semantic models by extracting metadata, generating documentation, and cataloging all model objects using pbi-cli. Invoke this skill whenever the user says "document this model", "what's in this model", "list everything", "data dictionary", "model inventory", "audit contents", "catalog", "describe the model", or wants to understand what objects exist in a semantic model.
Apply, inspect, and compare Power BI report themes and conditional formatting rules using pbi-cli. Invoke this skill whenever the user mentions "theme", "colours", "colors", "branding", "dark mode", "corporate theme", "styling", "conditional formatting", "colour scale", "gradient", "data bars", "background colour", "formatting rules", "visual formatting", or wants to change the overall look-and-feel of a report or apply data-driven formatting to specific visuals.
Sync your Beehiiv audience to a local database and answer growth questions offline in one command. Trigger phrases: `check my beehiiv growth`, `subscriber sources`, `which send time works best`, `compare my publications`, `lookup subscriber email`, `use beehiiv`, `run beehiiv`.
Sync your Fathom meetings once, then search, analyze, and act on them forever — offline, at scale, without burning API quota. Trigger phrases: `what did I promise in my calls`, `how often has pricing come up in meetings`, `brief me on my Acme calls`, `which team members are in too many meetings`, `find a meeting where we discussed X`, `search my fathom meetings`, `use fathom`, `run fathom-pp-cli`.
Onboard prek (Rust-powered pre-commit) into any project and suggest hooks tailored to the language/framework. Use when the user says "add prek", "set up pre-commit hooks", "configure prek", "what hooks should I use", or when you notice a project without a prek.toml that would benefit from pre-commit checks. Also trigger when the user wants to add new hooks to an existing prek.toml, audit their hook config, or migrate from pre-commit to prek. Covers Rust, Python, TypeScript/JavaScript, Go, Ruby, and Shell projects. Do NOT use for husky, lint-staged, or CI pipeline hook configuration — this skill is specifically for prek.
Build and manage a product roadmap for a solopreneur business. Use when deciding what to build next, prioritizing features, planning product development over quarters, communicating plans to customers or stakeholders, or managing scope and expectations. Covers prioritization frameworks, roadmap structure, customer feedback integration, and saying no to feature requests. Trigger on "product roadmap", "what to build next", "feature prioritization", "roadmap planning", "product strategy", "feature requests".
Project planning and feature breakdown for Python/React full-stack projects. Use during the planning phase when breaking down feature requests, user stories, or product requirements into implementation plans. Guides identification of affected files and modules, defines acceptance criteria, assesses risks, and estimates overall complexity. Produces module maps, risk assessments, and acceptance criteria. Does NOT cover architecture decisions (use system-architecture), implementation (use python-backend-expert or react-frontend-expert), or atomic task decomposition (use task-decomposition).
Generate structured planning documentation for web projects with context-safe phases, verification criteria, and exit conditions. Creates IMPLEMENTATION_PHASES.md plus conditional docs (DATABASE_SCHEMA, API_ENDPOINTS, UI_COMPONENTS, CRITICAL_WORKFLOWS). Use when: starting new Cloudflare Workers/React projects, adding major features to existing apps, breaking large work into manageable phases, or need verified planning before coding begins.
Software project effort estimation assistant. Outputs three-point estimates (optimistic/most-likely/pessimistic values with confidence intervals), T-shirt sizes, or Function Point Analysis (FPA) counts. Triggered when users ask 'how long will this feature take,' need to assess project workload, perform PERT estimation, T-shirt sizing, FPA, sprint planning, or quote-based effort breakdowns.
Enhance user prompts by analyzing project context (code structure, dependencies, conventions, existing patterns). Use when users provide brief development requests that would benefit from project-specific context to generate more accurate, contextually-aware prompts.
Produces self-contained HTML/CSS mockups and wireframes from design tokens and page specs — the output is always a viewable .html file, not guidance or code. Use when the request is to see a design, make a mock, build or show a prototype, create a wireframe, render a preview, or visualize what a page looks like before writing production code. Reads DESIGN.md tokens and JOURNEY.md page specs when present; uses greyscale wireframe defaults when absent. Renders via the browser MCP and returns a screenshot path when connected; emits the .html with an open note when not. Not for: choosing or defining fonts, colors, visual identity, or design tokens (use core design); critiquing, auditing, or reviewing an existing design (use core audit); planning IA, flows, or page specs (use journey); building a design token system or component library (use design-systems).
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.