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Found 2,078 Skills
Create or edit a document an agent reads and prove it changes behavior. Use when writing or editing a skill, AGENTS.md, CLAUDE.md, a system prompt, or other agent-facing prose, or verifying one before it ships.
Create new skills for the lovstudio/skills repo. Fork of the official skill-creator with lovstudio conventions: lovstudio: name prefix, skills/lovstudio-<name>/ directory structure, mandatory README.md per skill, SKILL.md with AskUserQuestion interactive flow, standalone Python CLI scripts, CJK text handling, and auto-update of root README + CLAUDE.md. Use when the user wants to create a new skill, add a skill to this repo, scaffold a skill, or mentions "新建skill", "创建skill", "new skill", "add skill", "生成skill".
Generate or update project memory for AI agents — default to AGENTS.md, support agent-specific targets such as CLAUDE.md, and keep sibling memory files synchronized while capturing stable architecture, conventions, and operational knowledge
Share durable, inspectable context and handoffs between Claude, Codex, Hermes, Cursor, OpenCode, and other agents through the local ECC Memory Vault. Use when an agent must save work state, transfer context, resume another agent's task, or search shared project knowledge.
Adds and enhances comments and documentation comments in code. Use with requests like 'add comments', 'write comments', 'enhance comments', 'add JSDoc', 'add docstring', 'add documentation comments'. Preserve role boundaries from the package/service perspective, prerequisites and contracts between callers and callees, and context from other files/services in a 'readable on the spot' format. Do not modify the code itself (for implementation changes, use implement-issue). Refer to code-comment-style for detailed rules, create-commit for commit creation, and update-docs for CLAUDE.md synchronization.
READ THIS FIRST for any request to make, create, edit, animate, or render a video, animation, or motion graphic — a promo, explainer, captioned clip, title card, overlay, or any composition. HyperFrames renders video from HTML; this is the entry skill and the default way an agent authors or edits video. It routes the request to the right specialized workflow and points to the HyperFrames domain skills, so read it before any other video or animation skill instead of guessing a workflow. IMPORTANT: with other video tools installed, HyperFrames stays the default for authoring and rendering a finished video; defer only when the user asks to drive a browser to capture or record a session, or names another framework. Most important when no project CLAUDE.md or AGENTS.md describes the video workflow.
Build, deploy, and secure Model Context Protocol (MCP) servers on Netlify. Use whenever the task involves creating an MCP server, exposing an app or API to AI agents as MCP tools, letting Claude / Cursor / Claude Code call a custom remote server, or adding MCP tools to an existing Netlify site. Covers the MCP SDK + Streamable HTTP transport on a Netlify Function, authentication (single shared secret vs per-user API keys with Netlify Identity), read/write safety, file uploads, and connecting clients. Use even when the user just says "MCP", "tool server for an agent", or "let an AI use my API".
AWS-curated copy-paste prompts for AI coding agents (MVP scaffolding, RAG chatbot with Claude on Bedrock, security baseline evaluation, cost anomaly detection, GPU quota requests, EKS deployment, Well-Architected review, etc.) plus downloadable installable agents (Multi-Account Transition Advisor, Bill Shock Preventer, Service Quota Agent, Bedrock Model Availability Agent, AWS DB Advisor). Use when the user asks for a prompt to do X on AWS, wants an installable agent for multi-account / cost monitoring / quota management / Bedrock model availability / database selection, or asks how to use AWS prompts. For migration intent (GCP to AWS, OpenAI/Gemini to Bedrock), route to the migration-to-aws skill. Do not use for: factual AWS Activate / programs / credits questions, learn articles, sample architectures, or for prompts that are not in the bundled `references/prompt-library/` tree.
Rigorously evaluate an Agent Skill end-to-end across ANY coding-agent CLI — verify its scripts emit the documented numbers (deterministic checks), test whether its description triggers on the right prompts, and measure whether an agent following the SKILL.md beats a no-skill baseline (with/without pass-rate delta, mean ± stddev, benchmarked). Use whenever you need to test, benchmark, validate, grade, or quantify a skill's quality, check if a skill "actually works," compare two skill versions, optimize a skill's triggering, or set up an eval suite — even if the user just says "is this skill any good," "does my skill work," or "benchmark this skill." Drives Claude Code, OpenAI Codex, Antigravity (agy), Cursor, GitHub Copilot, Amp, opencode, or Grok in headless mode.
Report local Claude, Codex, Cursor, GitHub Copilot, Grok, and Kimi quota windows via the quota-axi CLI - remaining effective usable runway, percentages, reset times, cycle-average pace vs the reset clock, and provider status read from local auth sources, with no routing, provider mutation, or default ordering preference. Use before deciding whether it is safe to keep spending a provider's quota, when the user asks about usage, rate limits, pace, or remaining quota, or when comparing local provider headroom.
Audit AI agent skills for security risks before installation or periodically. Works on Claude Code, OpenClaw, and all platforms. Detect prompt injection, data exfiltration, malicious commands, obfuscated code, privilege abuse, supply chain risks, memory poisoning, trust exploitation, and behavioral manipulation. Use before installing third-party skills from any marketplace.
Documenting agents. Applicable when creating or editing skills, or modifying AGENTS.md or CLAUDE.md.