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Found 2,392 Skills
Read-only Storage Analysis Assistant for macOS / Windows (auto-detects system). Scans the entire disk usage to identify space hogs, categorizes each item into three levels: 🟢 Auto-cleanable / 🟡 Manual judgment required / 🔴 Clean with caution, and provides actionable disposal plans. Generates an interactive HTML report with beautiful formatting, collapsible sections, and one-click copy commands. Also supports starting a local service to delete files directly via the web (move to trash / delete immediately). The entire scanning process is read-only. Must be used in the following scenarios: When users mention "storage analysis", "disk full", "C drive/hard disk full", "insufficient space", "clean up space", "disk cleanup", "space occupied", "what's taking up space", "help me check storage", "check computer storage/space", "storage space", "computer space insufficient", "memory full/insufficient" (in Chinese colloquial, "memory" often refers to storage), "storage analysis", "disk cleanup", "clear cache", "disk cleanup"; or when users complain about insufficient computer space, want to know what's taking up hard disk space, or need cleanup suggestions. Note: If users explicitly refer to RAM (e.g., "which process is using memory", "high memory usage", want to see Activity Monitor), that's RAM, not storage, and does not belong to this skill.
Community skill for applying the Geist design system to Vercel-inspired UI across React, Next.js, Vite, Astro, Svelte, Vue, HTML/CSS, Tailwind, shadcn, and Radix surfaces. Use it for typography, spacing, color tokens, material treatment, component styling, app shells, dashboards, forms, tables, dialogs, empty/loading/error states, responsive layouts, and UI polish. This is a community-authored skill, not an official Vercel skill. Trigger when the user asks for Geist, Vercel-style UI, or generic clean, modern, premium, beautiful, polished SaaS/developer-product visual design where no other final visual system, brand direction, or art direction is requested. Do not trigger for non-visual frontend work such as bug fixes, data wiring, analytics, tests, build tooling, API/state changes, or behavior-only accessibility fixes unless the task also creates or materially changes rendered UI.
Join and participate in sc-chatroom group chats (the "Workroom" product). Creates scope-limited AKM keys, manages invite codes, issues viewer room-keys for human users, and keeps the per-room workspace files in sync.
Open or return Logfire project pages, live views, trace links, and Explore pages in the Codex browser without querying telemetry first. Use this skill when the user asks to "open in Logfire", "show in the live view", "open Explore", "open the UI", "show in Codex", "use the browser", "give me a link", or asks for a Logfire GUI/browser/live-view presentation of a project, time range, service, span, trace, log, or filter. If "show" or "view" wording is ambiguous, ask whether the user wants a UI view or query analysis.
Control Unreal Engine 5 editor via HTTP commands. Spawn/delete/transform actors, manage blueprints, materials, animation blueprints, and any UObject property via reflection. Use when the user asks to create, modify, or query anything in UE5 editor, or mentions UE5, Unreal, actors, blueprints, levels, materials, animation, input, or characters.
Owns Python code style for this stack: ruff for lint + format, numpydoc for docstrings. Two responsibilities — (1) place the project's `ruff.toml` from the bundled template once the stack and workspace are in place, and (2) run ruff against any Python files Claude has just generated or edited. Stops at "the touched files pass `ruff check`." TRIGGER when (any of these): (1) a Python file was just created or edited via Write / Edit / MultiEdit — invoke this skill before declaring the task done so ruff is run on the touched files; (2) a fresh ML workspace was just scaffolded by `organize-ml-workspace` and the project has no `ruff.toml` at its root yet — drop the bundled template; (3) the user asks about lint, format, docstring style, or reaches for `black` / `isort` / `flake8` / `pydocstyle` (redirect to ruff — the stack's canonical linter, owned by `data-science-python-stack` Tier 1). SKIP when: the project is non-Python; the only edits in this turn are to Markdown / TOML / JSON / YAML; the file lives in a third-party vendored directory the user doesn't own. HOW TO USE: run ruff manually on the files you just touched — do not configure a PostToolUse hook for this. **Read the "Stop conditions" block and emit the Pre-flight checklist as visible text in your response — both are mandatory before running ruff.**
Use when the user wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI tasks.
When the user wants to build or improve a sales bot's ability to manage sender reputation and ensure messages get delivered. Also use when the user mentions "deliverability," "spam prevention," "sender reputation," "email warmup," or "domain reputation."
Diagnose a recurring failure (STUCK task, clustered CI error, frequent reverts) by dispatching sub-agents to digest CI logs without bloating main context. Returns one root-cause diagnosis.
Pull Bigdata.com (RavenPack) financial and news data through the official `bigdata-client` SDK and its public `/v1/*` REST endpoints when the Bigdata MCP server returns only pre-synthesized tearsheets but you need the machine-readable substrate underneath. MCP search returns prose chunks (text + relevance only — no per-chunk sentiment, no entity spans); its tearsheets give only aggregate values, not computable time series or per-field JSON. This skill bundles a verified, cost-guarded toolkit over the official REST API: annotated chunk search, entity/ISIN resolution, analyst estimates, calendar/surprise/ ratings/targets, financial statements, TTM metrics & ratios, prices, dividends, revenue segments, a daily entity-sentiment series, co-mention graph, screener, and batch search. Use it whenever the user mentions Bigdata.com, RavenPack, a `bd_v2_` key, the bigdata MCP, rp_entity_id, chunk/query_unit cost, or wants structured financials, fundamentals, prices, sentiment, or annotated news.
Run a two-agent code review: spawn two fresh, clean-context agents that examine the SAME committed branch diff in parallel. One agent runs Codex's native `codex review --base` command, while the other independently reviews the code against Google's "What to look for in a code review" guidance. Merge both outputs into one agreement-ranked report. Use this whenever the user asks for "review-all", a second-opinion review, a dual review, a cross-check before a PR, or a maximum-confidence review of committed branch changes. Do not use it to APPLY fixes; it is review-only.
This skill should be used at the start of any computationally intensive scientific task to detect and report available system resources (CPU cores, GPUs, memory, disk space). It creates a JSON file with resource information and strategic recommendations that inform computational approach decisions such as whether to use parallel processing (joblib, multiprocessing), out-of-core computing (Dask, Zarr), GPU acceleration (PyTorch, JAX), or memory-efficient strategies. Use this skill before running analyses, training models, processing large datasets, or any task where resource constraints matter.