Total 58,956 skills
Showing 12 of 58956 skills
Create a container-in-container layout system using nested frames. Use an outer centered container with visible vertical boundary lines and corner markers. Inside, place inner containers inset from the edges, each with its own background and rounded frame. Technique: outer container defines global bounds, inner containers use padding to create inset spacing, layered frames (border + background) to separate levels, and consistent spacing between outer frame and inner blocks.
Unified automation entry point. Covers browser automation (Playwright) and Windows desktop application automation (OpenReverse). Browser scenarios: Open web pages, click, fill forms, crawl, take screenshots, automated login, penetration testing page interaction. Desktop scenarios: Operate GUI tools like IDA/x64dbg, Windows UI Automation, vision-driven interaction, desktop application network packet capture. Trigger keywords: browser automation, desktop automation, open web page, fill form, crawl, take screenshot, automated login, Playwright, agent-browser, headless, OpenReverse, UIA, CUA, desktop operation, Windows automation.
Creates task-oriented technical documentation with progressive disclosure. Use when writing READMEs, API docs, architecture docs, or markdown documentation. Also use this skill at the END of any completed reverse engineering, penetration testing, CTF, or security analysis task to generate a formal report in the user's project directory. Trigger keywords: 写报告, 写文档, 出报告, writeup, 技术文档, report, documentation.
Collect search results from Amazon — product titles, prices, ratings, URLs, sponsored flags. Use when the user wants to collect listings matching a keyword or category.
Use when the user wants to find posts, videos, reels, shorts, tweets, or social content that overperformed versus a creator, brand, or competitor baseline. Finds outliers, explains why they worked, extracts hooks and formats, and produces a practical swipe file.
Use when the user wants a social listening report about what people are saying about a brand, person, product, topic, category, or niche across public social platforms. Produces cited themes, sentiment caveats, notable posts, and recommended actions.
Use when the user wants to research competitors' social media strategy, compare brands or creators, find what content is working in a niche, identify content gaps, or produce a practical social strategy brief from public social data.
Full ceremony mode for the whole suite. Run /deep before risky or ambiguous work; /deep off returns to fast-first.
Internal support skill, the relentless interview loop other skills delegate to. Use only when another skill or the user explicitly triggers it, never on your own.
Query OpenRouter's Benchmarks API for model benchmark rankings and scores. Use when the user asks for benchmark-backed model selection, model rankings by coding/intelligence/agentic ability, Artificial Analysis or Design Arena ELO/win-rate results, benchmark citations, or wants to call GET /api/v1/benchmarks. Also use alongside openrouter-models when the user asks what model should power an app, product, workflow, or use case and benchmark evidence could inform or rule out part of the recommendation, including creative writing, editing, coding, design, agentic, or intelligence-heavy apps. Do not use for OpenRouter usage analytics, billing/spend analysis, generation metadata, provider uptime/latency, generic model pricing/capability lookup without any selection or benchmark-relevance decision, or creating an evaluation suite for a local app.
Decomposes a PRD into well-formed, engineer-ready tickets — Jira issues or GitHub issues. Use after a PRD exists, to turn its phases and user stories into a structured backlog. Works for a new codebase (MVP scope) or an existing one (epic scope).
Take a PRD and build a dark factory around it - a repository that takes work in as an issue and ships validated code out with nobody at the keyboard - one component at a time, into the user's actual repo. Covers the five components in construction order - the guidance layer, the validation harness, the workflow-driven repo, deployment, and the trigger that makes it autonomous - and is agnostic about which coding agent runs underneath (Claude Code, Codex, Archon, the Agent SDK, Cline, Goose, Amp, Pi). It encodes the AI coding process the user already runs rather than replacing it. Requires a PRD as input and deliberately does not write one. Use when the user wants to build a dark factory, an autonomous or self-driving repository, a software factory, an agent that ships its own code, an unattended or overnight coding loop, or asks how to get to level 4 or level 5 of AI coding autonomy; and when they mention dark factory, lights-out coding, autonomous PRs, or a repo that maintains itself.