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Found 621 Skills
Use when the user wants to store, retrieve, search, or manage files in agent-fs — an agent-first filesystem backed by S3. Triggers on: "save this to agent-fs", "find that file", "store this document", "search agent-fs", "list my files", "show version history", "revert file", "set up agent-fs", "get a signed url", "share this file", "manage members", "invite user", "list members", "remove member", "update role", file persistence for agents, shared agent filesystem, or any mention of the agent-fs CLI. Also use when the user needs to manage drives, manage org/drive members, generate presigned URLs, check recent activity, or use semantic search across stored files. Also use when the user wants to run SQL over stored data files ("query this csv", "sql over my files", "duckdb", "aggregate the parquet file", "query the sqlite db", "join these spreadsheets"). Also use when the user wants to mount or unmount agent-fs as a Linux FUSE filesystem ("mount agent-fs", "fuse mount", "fuse", "remote mount", "sandbox mount", "expose drives as files", "use cat/grep/mv on my agent-fs files", "umount the drive", "mount a remote drive", "mount from sprite", "mount from e2b", "mount from hetzner"). Also use when the user wants to use agent-fs as a just-bash filesystem. Also use when the user wants to set up agent-fs without Docker or S3 ("local filesystem backend", "filesystem storage", "no docker", "onboard --filesystem", "store files on disk"). If the user mentions agent-fs in any context, always consult this skill.
Identify stocks where market sentiment is significantly more negative than fundamentals warrant — the gap between narrative and reality. Use when the user asks to find contrarian opportunities, stocks with sentiment-fundamental misalignment, oversold but fundamentally strong companies, stocks punished by negative narratives, or wants to analyze whether market fear is justified for specific stocks or sectors.
Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stores), and the cognitive architectures that organize them. Key insight: Memory isn't just storage - it's retrieval. A million stored facts mean nothing if you can't find the right one. Chunking, embedding, and retrieval strategies determine whether your agent remembers or forgets. The field is fragm
Adaptive Kotlin/Spring backend quiz with 5 questions. Difficulty adjusts based on your answers. Use when reviewing or testing your backend knowledge.
Use when making high-stakes decisions under uncertainty that require stakeholder buy-in. Invoke when evaluating strategic options (build vs buy, market entry, resource allocation), quantifying tradeoffs with uncertain outcomes, justifying investments with expected value analysis, pitching recommendations to decision-makers, or creating business cases with cost-benefit estimates. Use when user mentions "should we", "ROI analysis", "make a case for", "evaluate options", "expected value", "justify decision", or needs to combine estimation, decision analysis, and persuasive communication.
Use when the user wants to verify their understanding of a branch's code changes by being quizzed on runtime behavior, assumptions, failure points, and edge cases instead of just reading diffs
Manage your agentcash wallet and call any x402-protected API with automatic payment. No API keys, no subscriptions — just a funded wallet (USDC on Base). USE FOR: - Checking wallet balance before API calls - Redeeming invite codes for free credits - Getting deposit address for USDC - Discovering endpoints and pricing on any x402-protected origin - Making paid API requests via the agentcash CLI - Troubleshooting payment failures TRIGGERS: - "balance", "wallet", "funds", "credits" - "redeem", "invite code", "promo code" - "deposit", "add funds", "top up" - "discover", "endpoints", "what APIs", "pricing" - "insufficient balance", "payment failed"
Add a new gameplay feature to your game — just describe what you want
AI Agent native API provider — no API keys, no signups, no subscriptions. Just pay with USDC per request via x402 to instantly access Twitter, Instagram, and more.
Fast-track GTM value preview for new users. Runs gtm-analytics-audit and gtm-strategy back to back and outputs the top 5 tracking opportunities with business rationale and effort estimates. No implementation, no DOM changes. Just a clear answer to "what should I track and why". Trigger on - "quickstart", "what should I track", "show me tracking opportunities", "quick GTM overview", "I'm new to GTM", "where do I start".
Interact with GitLab via the glab CLI. Supports five MR workflows — Read (summarize), Review (full code/security/QA review), Fix (review + implement), CI Fix (fix pipeline failures), and Feedback (address review comments). Trigger whenever the user provides a GitLab MR URL or says anything like "อ่าน MR", "ดู MR", "check MR", "review MR", "ช่วย review MR นี้", "ตรวจ MR", "แก้ตาม MR", "fix MR", "fix CI", "fix pipeline", "แก้ pipeline", "แก้ตาม comment", "แก้ตาม feedback", "address feedback", or just pastes a GitLab MR URL. Also supports listing MRs, viewing MR status, checking CI/CD pipelines, approving MRs, and other glab operations. Trigger on "check pipeline", "list open MRs", "pipeline failed", or any GitLab-related task.
Convert text to speech (TTS). Powered by the VolcEngine Doubao Text-to-Speech API, it supports streaming synthesis, multiple voice timbres, adjustments to speech rate/pitch/loudness, Markdown syntax filtering, and LaTeX formula broadcasting. Use this skill when users need to convert text to speech, generate reading audio, dubbing, narration, broadcasts, or mention terms like 'text-to-speech', 'TTS', 'speech synthesis', 'reading aloud', or 'dubbing'.