Agent Skills

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name: react-native-dev

description: React Native and Expo development guide covering components, styling, animations, navigation, state management, forms, networking, performance optimization, testing, native capabilities, and engineering (project structure, deployment, SDK upgrades, CI/CD). Use when: building React Native or Expo apps, implementing animations or native UI, managing state, fetching data, writing tests, optimizing performance, deploying to App Store/Play Store, setting up CI/CD, upgrading Expo SDK, or configuring Tailwind/NativeWind.

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name: shader-dev

description: Comprehensive GLSL shader techniques for creating stunning visual effects — ray marching, SDF modeling, fluid simulation, particle systems, procedural generation, lighting, post-processing, and more.

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name: slide-making-skill

description: Implement single-slide PowerPoint pages with PptxGenJS. Use when writing or fixing slide JS files: dimensions, positioning, text/image/chart APIs, styling rules, and export expectations for native .pptx output.

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name: vision-analysis

description: Analyze, describe, and extract information from images using the MiniMax vision MCP tool. Use when: user shares an image file path or URL (any message containing .jpg, .jpeg, .png, .gif, .webp, .bmp, or .svg file extension) or uses any of these words/phrases near an image: "analyze", "analyse", "describe", "explain", "understand", "look at", "review", "extract text", "OCR", "what is in", "what's in", "read this image", "see this image", "tell me about", "explain this", "interpret this", in connection with an image, screenshot, diagram, chart, mockup, wireframe, or photo. Also triggers for: UI mockup review, wireframe analysis, design critique, data extraction from charts, object detection, person/animal/activity identification. Triggers: any message with an image file extension (jpg, jpeg, png, gif, webp, bmp, svg), or any request to analyze/describ/understand/review/extract text from an image, screenshot, diagram, chart, photo, mockup, or wireframe.

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name: analyze-data-quality

description: Assess whether structured data, query results, dashboards, or analytical evidence are trustworthy enough to use. Use when the task is to check data quality, reconcile conflicting sources or metric definitions, or decide whether evidence is safe to cite.

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name: arxiv

description: Use this skill whenever the user wants to find, read, cite, track, download, or analyze academic papers on arXiv. That includes: searching papers by topic, author, category, or arXiv ID; fetching abstracts or full metadata; generating BibTeX citations; downloading PDFs; listing the latest submissions in a field (e.g. cs.AI daily digest); checking a paper's citation impact; finding who cites a paper, what it references, or related-paper recommendations. Trigger on mentions of 'arXiv', an arXiv ID (e.g. 2601.02780 or hep-th/0601001), an arxiv.org URL, 'paper search', 'literature review', 'find papers about X', 'cite this paper', or 'what's new in cs.LG'.

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name: build-dashboard

description: Build a source-backed dashboard or monitoring view with clear metrics, filters, visual hierarchy, definitions, refresh context, and QA.

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name: build-report

description: Build a durable analytical report with an answer-first narrative, evidence-backed findings, charts or tables, caveats, recommendations, and source context.

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name: claude-code

description: Operate Claude Code CLI (v2.1+) via the terminal only when the user explicitly requests Claude Code or names this skill. Covers print mode (-p), interactive tmux sessions, and background (--bg) orchestration.

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name: codex

description: Run, configure, and troubleshoot OpenAI Codex CLI in non-interactive headless environments. Use for Codex automation in Bash or PowerShell, native Windows or WSL2, shell scripts, CI/CD, Docker, Kubernetes, remote servers, agent harnesses, or batch jobs; for constructing `codex exec` commands; selecting sandbox and approval modes; consuming JSONL events or structured output; resuming sessions; passing prompts through stdin; and handling failures caused by unavailable interactive input such as `request_user_input`.

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name: compose-next

description: Use for multi-step feature work, bug fixes, or refactors where requirements need to settle, a feature document should carry design + tasks + delivery evidence, and the change deserves independent review before merge. Use it only when the user explicitly requests this workflow, whether with `/compose-next`, by name, or in any other clear natural language; do not infer the request from task complexity alone. Not for one-shot edits, single-file tweaks, or answering questions — those need no orchestration overhead.

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name: create-data-context

description: Create, update, inspect, or repair Data Analytics semantic layers. Use when the user asks to save data context or create a semantic layer that future Data Analytics work can inspect and cite.

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name: data-analytics

description: Use this skill for quantitative product or business analysis: data quality checks, metric diagnostics, KPI design and reporting, dashboards, analytical reports, charts, notebooks, market sizing, semantic layers, and evidence-backed recommendations. Also use it whenever Data Analytics is explicitly invoked.

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name: deep-research

description: Deep research on any topic using parallel sub-agents and built-in tools only (WebSearch/WebFetch + free APIs, no keys). Use when the user asks for a thorough multi-source investigation with a cited report — "深度调研X"、"deep research"、"帮我全面研究一下"、"多方求证"、"写一份调研报告". NOT for simple lookups (single WebSearch suffices) and NOT for academic literature surveys (use auto-research skill instead).

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name: docx-official

description: Use this skill whenever a Microsoft Word (.docx) file is being produced, opened, transformed, or read. That includes: drafting reports, letters, contracts, RFPs, technical documents, or any long-form written deliverable; extracting text or structure from an existing Word file; filling a Word template with values; converting Word to PDF or plain text; splitting or merging documents; inspecting styles, headings, sections, tables, images, comments, or tracked changes. Trigger on mentions of 'Word doc', 'DOCX', 'Office document', a filename ending in .docx, or requests like 'turn this into a Word report'.

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name: drive-mimo

description: Use when developing or testing the MiMoCode repository and you need to programmatically drive another MiMoCode (mimo) process. Supports headless `mimo run` with JSON events and interactive TUI via tmux for behavior, integration, and visual regression testing. Covers an installed `mimo` binary or a dev build launched from source with `bun dev`; do not use it for ordinary MiMoCode task execution.

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name: effect

description: Answer questions about the Effect framework

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name: grok-build

description: Reference and workflow guidance for the Grok Build CLI (`grok`), including interactive and headless runs, authentication, sessions, worktrees, permissions, sandboxing, MCP servers, plugins, inspection, updates, and automation output. Invoke only when the user explicitly requests the `grok-build` skill, explicitly asks to use Grok Build CLI, or an already-selected workflow requires Grok Build; do not invoke for general coding, generic shell tasks, or other agent CLIs.

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name: html-to-video-pipeline

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name: learn-everything

description: Turn an uploaded PDF, paper, book chapter, document, URL, or user-provided topic into a structured, interactive learning course. Use when the user wants to learn, study, understand, master, review, or practice a subject chapter by chapter; asks for a tutorial or curriculum from source material; wants exercises, quizzes, answer grading, hints, spaced review, or a final assessment; or says "teach me this", "learn this PDF", "分章节教学", "带我学", or similar; or returns to continue a previous course ("continue my course", "接着上次学") or supplies a saved course-state file or state block. Adapt explanations and practice to the learner's level, preserve page or section references for documents, and teach incrementally rather than dumping all content at once.

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name: loop

description: Schedule a prompt to fire on a fixed cadence (recurring loop). Use when the user asks to "run X every N minutes/hours/days", "loop X", "babysit Y", "be proactive about Y every N", or invokes `/loop` directly. Parses `[interval] <prompt>`, picks a clean cron expression, registers the job via the `cron` tool, and executes the prompt once immediately so the user sees activity without waiting for the first cron tick.

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name: mate

description: Create custom desktop pet (Mate) characters with spritesheet and manifest. Use when the user asks to 'create a pet', 'make a desktop companion', 'design a mate character', 'generate a spritesheet for my pet', or wants to customize their desktop buddy. Generates a WebP spritesheet + manifest.json that can be loaded by MiMo Desktop's Mate system.

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name: memory-search

description: Query the raw trajectory SQLite database directly when the built-in memory and history tools are insufficient. Use when you need structured analysis across sessions: finding repeated errors, grouping tool calls by pattern, verifying what was actually executed, or locating specific past commands/decisions that text search cannot surface. Provides the database schema, ready-to-use SQL query templates, and per-goal strategies.

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name: mimocode-docs

description: Use whenever the user asks about MiMoCode itself: features, TUI or CLI commands, keybindings, terminal compatibility, rendering glitches, TUI lag, SSH or remote rendering, agent modes (build / plan) and how to switch between them, configuration, file locations, providers, models, authentication, or custom OpenAI-compatible or Anthropic-compatible API endpoints. Especially trigger when a prompt supplies or asks to configure a base URL/baseURL, API key/apiKey, model name or ID, provider, Anthropic Messages API, or global/project mimocode.json/jsonc, or when the user asks how to enter or leave plan mode. Also trigger when a skill, task, subprocess, or external client needs to borrow this instance's models — the OpenAI-compatible /v1 chat endpoints every MiMoCode server serves, `mimo llm-server` task tokens, or how to expose a listening port for them. Use this skill to inspect existing config safely, make minimal changes, and verify them without guessing schema fields or model capabilities.