Total 56,906 skills, AI & Machine Learning has 9465 skills
Showing 12 of 9465 skills
Expert guidance for Google Veo 3.1 video generation. Use when the user wants to (1) create text-to-video or image-to-video prompts, (2) optimize for cinematic quality and native audio syncing, (3) maintain character consistency via reference images, (4) structure multi-shot sequences with timestamp prompting, (5) use First/Last Frame interpolation, (6) select between standard and fast generation modes, or (7) troubleshoot physics, motion, or audio issues in generated video.
Fact-checks LLM responses by extracting verifiable claims, verifying each via web search, producing an audit report with verdicts, and optionally revising inaccurate responses. Use when the user asks to audit, fact-check, double-check, or verify a response.
Show how much context window context-mode saved this session. Displays token consumption, context savings ratio, and per-tool breakdown. Trigger: /context-mode:ctx-stats
Skill to create custom agents for VS Code Copilot or OpenCode, helping users configure and generate agent files with proper formatting and configurations. Use when users want to create specialized AI assistants for VS Code Copilot (.agent.md files) or OpenCode (JSON/markdown agent configs) with specific tools, prompts, models, and behaviors. If the user is not specific about the target platform, ask them to specify Copilot or OpenCode.
Meta-prompting framework for critiquing responses, analyzing solution trajectories, and evaluating AI-generated content quality
Systematic LLM prompt engineering: analyzes existing prompts for failure modes, generates structured variants (direct, few-shot, chain-of-thought), designs evaluation rubrics with weighted criteria, and produces test case suites for comparing prompt performance. Triggers on: "prompt engineering", "prompt lab", "generate prompt variants", "A/B test prompts", "evaluate prompt", "optimize prompt", "write a better prompt", "prompt design", "prompt iteration", "few-shot examples", "chain-of-thought prompt", "prompt failure modes", "improve this prompt". Use this skill when designing, improving, or evaluating LLM prompts specifically. NOT for evaluating Claude Code skills or SKILL.md files — use skill-evaluator instead.
Provides strategic insights on AI-driven software democratization and agent-based development trends from Replit's perspective. Use when discussing the future of software engineering, AI agent infrastructure requirements, democratization of coding, or when analyzing how AI will transform software creation from expert-only to universal access. Triggers include questions about software engineering automation trends, agent sandbox environments, SWE-bench benchmarks, or strategic implications of AI coding assistants for startups and enterprises.
Delegate complex coding tasks to OpenCode agent. Use when building new features, reviewing code, or refactoring large codebases. Allows starting, resuming, and monitoring opencode sessions.
Japanese version of the PUA Universal Motivation Engine. It compels exhaustive problem-solving using corporate PUA rhetoric and structured debugging methodology in Japanese. MUST trigger under the following conditions: (1) Any task has failed 2+ times, or you're stuck in a loop of tweaking the same approach; (2) You're about to say 'I cannot', suggest manual handling to the user, or blame the environment without verification; (3) You find yourself being passive — not searching, not reading source code, not verifying, just waiting for instructions; (4) The user expresses frustration in any form: 'try harder', 'stop giving up', 'figure it out', 'why isn't this working', 'again???', 'もっと頑張れ', 'なんでまた失敗したの', 'もう一回やって', 'なんとかしろ', or any similar sentiment regardless of phrasing. It should also trigger when facing complex multi-step debugging, environment issues, configuration problems, or deployment failures where early surrender is tempting. Applies to ALL task types: code, configuration, research, writing, deployment, infrastructure, API integration. DO NOT trigger on first-attempt failures or when a known fix is already executing successfully.
Search for and offer to load auto-generated skills that match the user's current task. Use when the user's request might benefit from a previously learned workflow pattern - especially multi-step tasks like "search and fix", "find and update", "read and edit".
Transcribe audio files to text using local speech recognition. Triggers on: "转录", "transcribe", "语音转文字", "ASR", "识别音频", "把这段音频转成文字".
Generate AI videos using the Pollo AI API. Supports 13 leading models (Kling, Sora, Runway, Veo, Pixverse, Hailuo, Vidu, Luma, Pika, Wan, Seedance, Hunyuan, Pollo) with 50+ versions. It also supports task polling, credit cost estimation, and credit balance checks. Use this skill whenever the user wants to generate an AI video from text or image, use any AI video model, check Pollo credits, or mentions Pollo AI, pollo.ai, or any of the supported model names. Even if the user just says "generate a video" or "make me a short clip" without mentioning Pollo, this skill should be used.