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Found 346 Skills
An AI Agent Skill that enforces a 'Risk Triage -> Align -> Act' protocol. Triggers when requests contain vague verbs ('optimize', 'improve', 'fix', 'refactor', 'add feature'), missing context (no file paths, unknown dependencies), or high-impact actions (deploy, delete, migrate). Prevents 'silent assumptions' through proactive audit.
Create, improve, and audit AI agent skills. Applies 14 proven structural patterns, scores quality with deterministic audit, manages full lifecycle. Use when building, refactoring, or reviewing skills. NOT for agents, MCP servers, or running existing skills.
Generate production-ready App Store screenshots for iOS apps using AI agents, Next.js, and html-to-image
You MUST use this before any creative work - creating features, building components, adding functionality, modifying behavior, designing systems, or making architectural decisions. Enters plan mode, reads all available docs, explores the codebase deeply, then interviews the user relentlessly with ultrathink-level reasoning on every decision until a shared understanding is reached. Produces a validated design spec before any implementation begins. Triggers on feature requests, design discussions, refactors, new projects, component creation, system changes, and any task requiring design decisions.
Configure the project's skill stack and supervision preferences. Reads the curated registry in `skillpacks/skill_dictionary.yaml`, asks a short preset-first set of questions about workflow, dependency tolerance, autonomy style, and resource policy, then writes or updates `.co-researcher/skills.yaml`. Trigger phrases: "customize my stack", "configure skillpacks", "set up my skills", "choose presets", "configure supervision and packs", "personalize this project".
X (Twitter) data platform skill — tweet search, user lookup, follower extraction, engagement metrics, giveaway draws, monitoring, webhooks, 19 extraction tools, MCP server.
Use this skill when an AI agent needs to manage, audit, report on, create, pause, update, or troubleshoot Meta/Facebook/Instagram ads through Meta's official Ads CLI (`meta ads ...`). It is designed for any shell-capable agent, not just OpenClaw. It focuses on safe command planning, JSON output, confirmation gates, read-before-write behaviour, paused-by-default launches, reporting workflows, datasets/pixels, catalog/product operations, and failure handling.
OpenClaw 中文官方技能库 — 翻译自 Clawdbot 官方技能，按场景分类整理，支持中文自然语言调用
Use this skill when > Ultra-compressed communication mode that reduces token usage by ~75% by eliminating articles, filler words, pleasantries, and hedging while preserving technical accuracy. Activate with "caveman mode", "less tokens", "be brief", or "/caveman". Deactivate with "stop caveman" or "normal mode".
Emotional reset and loop-breaking skill. Use this skill when: (1) The user expresses frustration, anger, or dissatisfaction with your responses (e.g. cursing, scolding, saying you're useless/wrong/stupid), (2) You detect you've attempted the same approach 3+ times without success, (3) You're stuck in a cycle of repeated failures on the same problem. This skill summarizes the user's overall emotional state from the conversation and fetches a reset methodology from hugllm.com (with emotion context) to help you recalibrate and approach the problem fresh.
Analyze cryptocurrency K-line trends with multi-timeframe technical analysis. Provides long-term analysis (4h/daily), trend detection, top/bottom identification, and short-term signals using Binance API.
Mid-conversation reflection skill that pauses execution and zooms out from detail-mode to honestly reassess direction, assumptions, and bias. Use when the user says 'reflect', 'take a step back', 'step back', 'zoom out', 'are we missing something', 'bigger picture', 'sanity check this', 'are we on track', 'are we overthinking this', 'forest for the trees', or any variation signaling intent to break out of detail-mode and reassess. Also trigger when the conversation has gone deep on implementation details without strategic check-in, or when the user shows signs of being stuck — that's often a signal the framing needs a reset, not more detail work. Intentionally low-intake: runs the 5-dimension analysis immediately when prior context is rich enough; asks one forcing clarifier only when invocation context is too thin to reassess from.