Rabbit-Ivan
Community@Rabbit-Ivan
Rabbit-Ivan maintains a 79-skill registry spanning Lark/Feishu enterprise collaboration, frontend design systems, code-quality audits, and document/media generation.
Agent Skills by Rabbit-Ivan
Showing 79 vetted skills indexed across 1 GitHub repositories.
Rabbit-Ivan.agents
Documents repository structure and maintenance conventions for a centralized AI agent skills collection.
Rabbit-Ivanbenzenith-frontend-design2
Generates BenZenith-branded frontend pages with Next.js, React, Tailwind, and HTML/CSS.
Rabbit-Ivanlark-mail
Draft, send, read, and search Feishu mailbox emails via lark-cli commands.
Rabbit-Ivanplanning-with-files
Implements file-based planning with task_plan.md, findings.md, and progress.md for complex multi-step tasks.
Rabbit-Ivanai-reimbursement
Generates reimbursement approval documents and dark glassmorphism HTML infographics for AI tool subscriptions.
Rabbit-Ivanui-ux-pro-max
Searches a BM25-indexed database of UI styles, palettes, fonts, and stack guidelines for design decisions.
Rabbit-Ivanreact-component-diagnosis
Diagnoses a single React component across seven design dimensions with evidence-based scores.
Rabbit-Ivanlark-minutes
Retrieve Feishu Minutes metadata and AI-generated meeting artifacts via lark-cli.
Rabbit-Ivanremotion-best-practices
Provides domain rules and code patterns for building videos programmatically with Remotion in React.
Rabbit-Ivanhai-idea
Evaluates ideas and returns a verdict with scorecard, objection, reframe, and validation test.
Rabbit-Ivanhai-visual-report
Generates multi-section HTML reports with Mermaid diagrams from ideas, requirements, and reviews.
Rabbit-Ivanstatic-residential-ip-assessor
Assess whether an IP is static residential broadband using multi-source evidence and risk scoring.
Rabbit-Ivanneat-freak
Reconciles project documentation and agent memory against code and audits workspace rule compliance.
Rabbit-Ivanlark-openapi-explorer
Discovers and invokes native Feishu/Lark OpenAPI endpoints from official documentation.
Rabbit-Ivanlark-skill-maker
Creates reusable Skills that wrap lark-cli commands for Feishu OpenAPI operations.
Rabbit-Ivanlark-calendar
Manage Lark calendar events, attendees, freebusy queries, and meeting time suggestions via lark-cli.
Rabbit-Ivantheme-factory
Applies curated color and font themes to slides, docs, and HTML artifacts.
Rabbit-Ivanlark-workflow-standup-report
Generates daily schedule and pending task summaries from Lark calendar and task APIs.
Rabbit-Ivanlark-wiki
Manage Feishu wiki spaces and document nodes via lark-cli.
Rabbit-Ivanhai-ssot
Diagnose single-source-of-truth violations and produce numbered findings reports with file:line evidence.
Rabbit-Ivansora
Generate, remix, poll, and download Sora videos via the OpenAI Video API.
Rabbit-Ivandoc-coauthoring
Guides collaborative document drafting through context gathering, iterative refinement, and reader testing.
Rabbit-Ivanreadme-beautifier
Restructures and reformats messy README files without changing their content.
Rabbit-Ivanobsidian-markdown
Create and edit Obsidian Flavored Markdown with wikilinks, callouts, embeds, and properties.
Frequently Asked Questions About Rabbit-Ivan
FAQPage SchemaWhat tasks can I accomplish with Rabbit-Ivan's skill collection?âž
You can operate the full Feishu/Lark suite (mail, calendar, docs, sheets, Base, IM, tasks, wiki, drive, meetings), audit React components and code quality, draft PRDs and goal contracts, build designed frontend pages, convert office files to Markdown, and render Remotion or Sora videos.
Who are these skills designed for?âž
They target Feishu/Lark power users automating collaboration routines, frontend engineers seeking design-grade UI output, and developers or product managers needing structured code reviews, architecture critiques, PRD authoring, and documentation audits grounded in file:line evidence.
What are the prerequisites and dependencies for running these skills?âž
All lark-* skills require the lark-cli binary and initial setup via lark-cli config init plus auth login. The sora skill needs an OPENAI_API_KEY with Sora access, lark-whiteboard requires Node.js 18+, and remotion-render runs through the inference.sh Bash command.
Are these skills open-source, and what licenses apply?âž
Licensing is mixed. markitdown carries an MIT license, while xlsx, pdf, pptx, docx, and n8n-gen are proprietary with terms in LICENSE.txt. Theme-factory, canvas-design, brand-guidelines, and frontend-design reference their bundled LICENSE.txt files; most other skills state no explicit license.
How do the engineering-judgment skills like hai-idea, geju, and goudi work together?âž
They form a decision pipeline: hai-idea verdicts whether an idea deserves attention (Do/Validate/Kill), geju produces a bold direction judgment with a kill-list, goudi pressure-tests landing feasibility with a minimum first move and stop rule, and hai-goal converts the result into a verifiable phased goal document.