Skills
101,174 packaged capabilities and playbooks for agents. Install any of them with one command.
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Statistical arbitrage tool for identifying and analyzing pair trading opportunities. Detects cointegrated stock pairs within sectors, analyzes spread behavior, calculates z-scores, and provides entry/exit recommendations for market-neutral strategies. Use when the user requests pair trading opportunities, statistical arbitrage screening, mean-reversion strategies, or market-neutral portfolio construction. Supports correlation analysis, cointegration testing, and spread backtesting.
Analyze Android, Linux, and Chromium Perfetto traces with local trace_processor_shell evidence. Use for startup, scrolling or jank, input latency, ANR, CPU scheduling, memory or GC, Binder or IO, GPU or SurfaceFlinger, power or thermal, rendering-pipeline identification, trace capture guidance, scene reconstruction, and single- or multi-trace performance comparison.
Configure SSL/TLS break-and-inspect on next-generation firewalls and forward proxies to decrypt, inspect, and re-encrypt HTTPS traffic for malware and exfiltration detection, including deploying trusted CA certificates, managing exemptions for certificate-pinned apps, and privacy compliance. Use when setting up or auditing TLS inspection on network security devices to close the encrypted-traffic blind spot.
Plan a round of user interviews conducted by PostHog''s AI voice agent (a "robo interviewer") — the automated voice-agent interview product. Captures a UserInterviewTopic (who to target, what to ask, framing context, question list) and calls user-interview-topics-create. ONLY trigger when the user clearly wants an AI voice agent to actually run the interview calls (e.g. "set up robo user interviews", "have the voice agent interview these users"). Do NOT trigger for ordinary user research that does not involve the voice agent — finding or shortlisting users to talk to ("who''d be a good fit to interview about Y"), planning questions for a human-run interview, or analysing feedback are audience discovery, handled with normal data queries, not this skill. Also do NOT trigger for uploading a recorded interview audio file or browsing topics with user-interview-topics-list. When intent is ambiguous, first confirm what kind of research it is and whether they want an AI voice agent to conduct it (see Step 0).
Provides comprehensive guidance for Playwright testing including browser automation, test writing, page objects, and cross-browser testing. Use when the user asks about Playwright, needs to write E2E tests, automate browsers, or test web applications across browsers.
Govern Playwright TypeScript regression suites across many tests. Use when asked to plan, select, tier, execute, or optimize suites with risk/change analysis, tags, CI/CD, sharding, flaky-test management, or suite-health metrics; not for authoring one UI spec. Keywords: regression strategy, smoke tests, test selection, CI pipeline, flaky tests, test sharding, impact analysis, git diff.
Read any Substack publication as a local, full-text-searchable corpus — keyless for free posts, your own session for what you subscribe to. Trigger phrases: `archive this Substack`, `read this Substack post`, `search my Substack corpus`, `what's new in my newsletters`, `use substack-reader`, `run substack`.
Presentation creation, editing, and analysis. When Claude needs to work with presentations (.pptx files) for: (1) Creating new presentations, (2) Modifying or editing content, (3) Working with layouts, (4) Adding comments or speaker notes, or any other presentation tasks
[Hyper] Use this skill when the user asks to run pre-deploy checks, prove a repository is deploy-ready, or clear reproduced lint, typecheck, or build blockers before a release in a Node.js, Rust, or Python workspace. Readiness is proven only by a fresh full run of the bundled check scripts, and the skill never deploys. Do not use for a specific failed deployment log, a reproduced runtime application bug, new feature work, or the deployment action itself.
Design and build client-ready websites and mobile web apps in a working studio's proven house style, shown throughout on two fictional brands (AURA Heights, The Assembly): tinted grounds, editorial typography, obsessive specificity, and proof over promise. Carries the full working loop (brief, design contract, build, review gate, multi-lens audit, ship), two verified token systems, signature component patterns, proof-driven copywriting, real-photography rules, and a mobile web-app playbook (density budget, bottom tab bar, compaction). Trigger on "make it look expensive", "make it beautiful", "high end design", "client ready", "on brand professional", "use the prom design style", "design this landing page", "make it more like an app", "too much scrolling", "add real images", "the site looks cheap", "too generic", "ai slop". Not for inventing a fresh visual direction from a blank brief: this skill applies ONE proven aesthetic.
Execute, inspect, and rerun an existing Promptfoo redteam scan. Use for generated YAML, result exports, attack success rates, grader/target errors, filtered reruns, and CI gates. Use promptfoo-provider-setup for connections and promptfoo-redteam-setup for new scan plans.
Generate adaptive Python coding exercises for broad practical Python fluency: fundamentals, OOP, standard library, testing, CLIs, automation, backend services, FastAPI, Flask, AWS automation, data handling, and production scripting. Use whenever the user wants to practice Python, learn Python concepts, review Python code, debug Python programs, build backend APIs, automate AWS with Python, or mentions Python exercises, challenges, pytest, FastAPI, Flask, boto3, scripts, CLIs, or automation. Exercises must be created inside dated folders in /home/laborant/repos/python-practice. The skill tracks recurring mistakes and clarifying questions in the root learning-log.md; no progress tracker script or dynamic progress database is used.
Reads and writes Zotero libraries from Python with pyzotero 1.13.0 and the Zotero Web API v3: items, collections, tags, attachments, saved searches, full-text content, and BibTeX, CSL-JSON, and bibliography export. Also covers the pyzotero CLI and MCP server for a local Zotero 7. Use when fetching or searching library items programmatically; when creating, updating, or deleting references, collections, or tags; when uploading PDF attachments or downloading files; when exporting citations as BibTeX or CSL-JSON; when building research automation around a Zotero user or group library. Not for formatting citations in a manuscript or verifying references against external databases.
Prepare and seed test data for a feature into a target environment. Analyzes the feature's implementation, proposes data categories covering regular and edge cases, and populates the environment via existing seed mechanisms code access, REST, MCP. Use when the user asks to seed test data, populate a test or staging environment, prepare data for manual/QA testing of a feature, generate a dataset for a feature, or create fixtures in an environment.
Evaluates code quality through complexity analysis, lint results, code smell detection, and test health metrics. Use when assessing deployment readiness, configuring quality gates, scoring a codebase for release, or generating quality reports with pass/fail verdicts.
Strategic regression testing with test selection, impact analysis, and continuous regression management. Use when verifying fixes don't break existing functionality, planning regression suites, or optimizing test execution for faster feedback.
Iterative codebase quality audit with multi-agent validation and escalating-depth SEEK/VALIDATE/FIX/RECURSE cycle. Enforces fix-all-per-cycle rule — every confirmed finding must be fixed before moving to the next cycle. Use for quality audit, code audit, codebase review, technical debt audit, refactoring opportunities, module quality check, or architecture review.
Use this skill to grade a SKILL.md whenever the user wants to rate, audit, or score one. Triggers include "rate this skill", "grade this skill", "give my skill a letter grade", "audit my SKILL.md", "score this skill against best practices", or "is this SKILL.md up to spec", even if they don't use the word "rate". Returns a letter grade A-F, weighted category scores, and prioritized paste-ready patches. Do NOT use this skill for code review (see code-review) or for authoring a new skill (see generate-skill).
Record browser or Web UI interaction demos as optimized GIFs using the available browser-control workflow, optional Playwright Videos for higher capture frame rates, and deterministic encoding, then attach the GIF to a pull request with `gh --attach`; publication requires gh v2.99.0 or later, and a GIF over 5 MiB is split into parts. Use when asked to make, record, or generate a GIF that demonstrates a browser workflow, and for every pull request that changes product-user-visible GUI behavior, which MUST include a GIF recorded from the pull request's real server and model flow.
Create, improve and test agent skills for research workflows (paper writing, lab protocols, analysis pipelines, domain databases) that meet the Agent Skills specification and this repository's quality and security bar. Use when turning a repeated research task into a reusable skill, contributing a new skill to Research Agent Skills, rewriting an existing skill, writing trigger-accurate descriptions, or adding evals. Works alongside Anthropic's official skill-creator.
Design responsive layouts that maintain accessibility across screen sizes, zoom levels, and orientations. Use when designing responsive interfaces, testing zoom behaviour, or reviewing layouts across devices. Triggers on: responsive, zoom, reflow, breakpoint, mobile accessibility, screen size, orientation, viewport, 200% zoom, text scaling, layout shift, horizontal scroll.
Create polished, professional reveal.js presentations. Use when the user asks to create slides, a presentation, a deck, or a slideshow. Supports themes, multi-column layouts, code highlighting, animations, speaker notes, and custom styling. Generates HTML + CSS with no build step required.
Review data, issues, code, and git history; present options with effort and one-way/two-way door labels; recommend one path and name the right fix (explain if they differ). Use before implementing when a decision needs evidence-backed options.
Use when a founder wants a hard business decision debated by a council of world-class operators, says "roast room", "put this in the Roast Room", "founder council", "convene the council", "take this to the board", "what would Hormozi, Bezos, or Buffett say", "should I do X", or can't make up their mind on pricing, hiring, raising money, a new product, a partnership, a pivot, an event, or spending. A board of sub-agents, each built from one expert's public work (Bezos, Paul Graham, Hormozi, Gary Vaynerchuk, Dan Martell, Gino Wickman, and Buffett out of the box, plus any seat added with /newroaster), argue it over three rounds, then a Chair returns a scored verdict, the reasoning, the dissent, and next steps. Also does a one-seat consult ("ask the Hormozi seat"). Not /roast (generic personas, idea validation).
When the user wants to optimize delivery routes, solve vehicle routing problems, or minimize transportation costs. Also use when the user mentions "route planning," "delivery optimization," "VRP," "TSP," "multi-stop routing," "route sequencing," or "dispatch optimization." For fleet sizing and management, see fleet-management. For last-mile specific challenges, see last-mile-delivery.
FIRST stop for Salla app development — load before generic brainstorming or planning. Use when building, configuring, or debugging a Salla app, when the task is broad ("build a Salla app", "add X to my app"), or when unsure which Salla skill applies. Dispatches intent to the right skill and maps each Salla Partners MCP tool to its capability. For a specific subsystem (OAuth, webhooks, settings, billing, publishing…), go straight to its skill. Twilight themes (a separate product) → salla-theme-builder.
Per-merchant settings for a Salla app. Use when designing a settings schema, registering the form, or reading/writing merchant config. Covers the salla_settings form + optional Validation URL, supported-features declaration (publish-blocker for communication apps), seeding defaults on install, value read/write (POST is a full replace — send ALL keys), reacting to app.settings.updated (activates the app AND is the storage source of truth), and context.settings in App Functions. Admin API → salla-api-core; lifecycle → salla-app-lifecycle.
Generates publication-style scientific diagrams as raster PNG images from a natural-language prompt, using Nano Banana 2 via OpenRouter, then scores each image with Gemini 3.6 Flash against a document-type threshold (journal, conference, thesis, grant, preprint, poster, etc.) and regenerates up to twice. Writes versioned PNGs and a review_log.json. Use when drawing neural network architectures, CONSORT or PRISMA flowcharts, biological signaling pathways, system or block diagrams, or circuit schematics. Use when a figure needs a quality score and critique recorded for a paper, poster, or grant. Not for vector, PDF, SVG, or EPS output, or for data plots; use a plotting skill for those. Prompts leave the machine, so avoid unpublished or patient data.
Annotate and map the anatomy of any design. Identify visual hierarchy, spacing systems, color roles, and tension points through clinical analysis. Use when doing formal design audits, teaching design analysis, or building structured observation skills.
This skill should be used when analyzing sector and industry performance charts to assess market positioning and rotation patterns. Use this skill when the user provides performance chart images (1-week or 1-month timeframes) for sectors or industries and requests market cycle assessment, sector rotation analysis, or strategic positioning recommendations based on performance data. All analysis and output are conducted in English.
Reviews and hardens AI agents, LLM apps, RAG, tool-calling and coding agents: prompt injection, tool permissions, approval gates, model-output sinks, AI data handling, safety regression tests. Use where a model's text can trigger actions or touch data. Not for non-AI appsec.
Repository-grounded threat modeling that enumerates trust boundaries, assets, attacker capabilities, abuse paths, and mitigations, and writes a concise Markdown threat model. Trigger only when the user explicitly asks to threat model a codebase or path, enumerate threats/abuse paths, or perform AppSec threat modeling. Do not trigger for general architecture summaries, code review, or non-security design work.
Writes product promo animation prompts (Motion Graphics Prompt) for the Seedance 2.0 video generation model. Generates 15-second single-take motion image prompts, supporting 4 aesthetic styles (Apple/Microsoft/Bauhaus/Vercel). Supports the reference image (垫图) mode, automatically marking image placeholders. After generating prompts, videos can be generated directly via the 即梦 Dreamina CLI (installation status auto-detected). TRIGGER when: the user needs to generate Seedance video prompts, product promo animation prompts, motion graphics prompt, or mentions "Seedance", "视频提示词", "产品动画", "宣传视频提示词", "video prompt". Keywords: Seedance, 视频提示词, video prompt, motion graphics, 产品动画, 宣传动画, 垫图, Dreamina
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.