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OpenSenseNova

SenseNova-Skills

Modular SenseNova skills for building AI-powered office assistants and productivity workflows

$npx skills add OpenSenseNova/SenseNova-Skills
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84 skills in this pack.

68
OpenSenseNova

sn-code-video

Create and revise code-driven videos with Canvas, SVG, HTML/CSS, Three.js, Remotion, Manim, or p5.js, including sound, deterministic frame capture, visual review, and MP4 verification. Use…

Pack6.1k4kVideo
68
OpenSenseNova

sn-deep-research

用于用户请求深度研究、系统性研究、竞品分析、方案对比、趋势分析或事实核查时。**遇到以下任一情况就主动使用本 skill,不要自行搜几条就回答**:①用户出现触发词:深度研究 / 深度调研 / 深入研究 / 全面研究 / 系统研究 / 调研 / 调查 / 尽调 / 行业研究 / 市场研究 / 竞品分析 / 政策研究 / 技术研究 / 趋势研究 / 事实核查 / 写一份研究报告…

Pack6.1k4kResearch
68
OpenSenseNova

sn-image-base

Base-layer skill for the SenseNova-Skills project, providing low-level APIs for image generation, recognition (VLM), and text optimization (LLM). This skill does not preprocess inputs; it…

Pack6.1k4kImages & art
68
OpenSenseNova

sn-motion-html

Build continuous-shot motion-driven HTML stories from a subject or narrative, including research, story structure, consistent AI stills, Seedance scene and connector clips, interface…

Pack6.1k4kFrontend
68
OpenSenseNova

sn-ppt-dazzle

需要把演示 / 幻灯片 / PPT / slides 做成单文件 HTML 动态 deck(动效、跨页过渡、键盘翻页、1280×720)时使用。本 skill 非入口:使用前必须先确认 sn-ppt-entry 与 sn-ppt-story 两个前置 skill 可用,依次执行 entry(建 DECK_DIR / task_pack.json)→ story(生成…

Pack6.1k4kFrontend
68
OpenSenseNova

sn-ppt-standard

仅在 `sn-ppt-entry` 与 `sn-ppt-story` 已准备绝对 `DECK_DIR` 和 `outline.md` 后使用;生成每页独立 HTML(1600×900)、渲染 PNG、逐页讲稿、`present.html`,并按 `static_postprocess` 选择生成由 Standard 自有 exporter 转换的…

Pack6.1k4kFrontend
68
OpenSenseNova

sn-ppt-workbench

Use when the user asks to open, preview, inspect, or visually edit an existing SenseNova HTML presentation in the PPT Workbench, using an explicit deck_dir or the latest deck in the current…

Pack6.1k4kCoding
68
OpenSenseNova

sn-search-academic

用于学术调研、论文精读、相关工作梳理、百科知识查询和引用链追溯。

Pack6.1k4kResearch
66
OpenSenseNova

sn-da-image-caption

图片理解与数据提取 skill。当图片文件(.png/.jpg/.jpeg/.gif/.webp/.bmp)是主要输入且用户需要理解、提取数据或分析图片内容时使用。提供预配置的 caption 脚本(scripts/caption.py),通过 vision 模型将图片转为文本描述,无需额外配置 API Key。覆盖:(1) 通过 scripts/caption.py…

Pack6.1k4kVideo
66
OpenSenseNova

sn-infographic

Generates professional infographics with various layout types and visual styles. Analyzes content, recommends layout and style, and generates publication-ready infographics. Use when user…

Pack6.1k4kDesign
66
OpenSenseNova

sn-ppt-entry

Use when a user asks to create a presentation, slide deck, PPT, or PPTX from a query and optional files, or to resume an existing SenseNova presentation task.

Pack6.1k4kPresentations
65
OpenSenseNova

sn-image-doctor

Environment diagnostic skill for SenseNova-Skills project. Checks that sn-image-base is properly installed and configured, validates dependencies and environment variables. Prompts user to…

Pack6.1k4kImages & art
64
OpenSenseNova

sn-da-excel-workflow

Excel 数据分析多步编排器。覆盖:(1) 读取多 Sheet Excel 文件并统计行数,(2) 大文件检测(≥10k 行自动 Parquet 优化),(3) 数据清洗(缺失值、文本标准化、无效字符),(4) 条件筛选与分类提取,(5) 跨 Sheet 统计聚合,(6) 导出 Excel/CSV 并提供下载链接。覆盖从数据读取到报告生成全流程,按步骤编排…

Pack6.1k4kData analysis
64
OpenSenseNova

sn-da-large-file-analysis

万行以上 Excel 数据集的高性能分析引擎。提供 openpyxl read_only 流式读取(iter_rows 支持 10 万行以上)、Parquet 转换加速、内存优化、分块处理和大文件写入模式。**遇到以下任一情况就主动使用本 skill**:①数据行数 ≥ 10k(由 sn-da-excel-workflow 的行数评估步骤触发);②用户出现触发词:大文件 /…

Pack6.1k4kData analysis
64
OpenSenseNova

sn-deepresearch-cli

一键启用 SenseNova-Skills-DeepResearch,用于行业与市场研究、竞品分析、政策或技术调研、商业尽调、趋势分析、方案对比、事实核查,以及研究报告、白皮书等交付场景。用户提出深度研究、调研、调查、尽调、research/deepresearch,或任务需要跨来源取证、多维度比较和交叉验证时主动使用;Skill 会完成…

Pack6.1k4kCoding
64
OpenSenseNova

sn-image-imitate

Generates a new image that imitates the style of a reference image while updating content based on user intent. Uses a three-stage pipeline: image annotation (long caption), caption…

Pack6.1k4kImages & art
64
OpenSenseNova

sn-image-resume

Generates a designed portfolio-resume image from resume content provided in conversation text. Extracts optional style instructions, converts the resume into a fixed portfolio-resume layout…

Pack6.1k4kImages & art
64
OpenSenseNova

sn-ppt-creative

Use when a prepared PPT task with a current outline.md should be generated as an image-first presentation with one 16:9 image per slide and optional PPTX packaging.

Pack6.1k4kPresentations
64
OpenSenseNova

sn-ppt-tools

Use when another PPT Skill needs web search, image search or download, or image generation and the host Agent's equivalent native capability is absent or has failed.

Pack6.1k4kImages & art
63
OpenSenseNova

sn-md-to-html-report

将 Markdown 报告、研究笔记、行业分析、战略备忘录、技术白皮书、复盘、周报等长文档,重组并创作为有编辑判断、网页美感和证据秩序的自包含 HTML 专题页。用户要求“转成 HTML”“网页化报告”“美化报告”“做成专题页”“便于分享”“提升可读性/设计感”“把报告做成网页”时使用。必须先写 plan.md 再写 HTML,保留原文事实断言和结论强度,不套模板,不做机械…

Pack6.1k4kFrontend
63
OpenSenseNova

sn-ppt-doctor

Use when diagnosing PPT Skill setup or failures involving source parsing, Playwright or Chromium rendering, HTML-to-PPTX export, Workbench startup, or bundled search and image-tool…

Pack6.1k4kDocuments
63
OpenSenseNova

sn-search-code

用于查找代码示例、开源项目、GitHub Issue、技术问答、开发者讨论、HuggingFace 模型/数据集/Space。

Pack6.1k4kCoding
63
OpenSenseNova

sn-search-finance

用于搜索金融市场、证券、上市公司基本面、价格、K 线、披露文件、财经新闻、A 股数据、港股或全球 ticker,可使用 yfinance、mootdx、API 脚本或 browser-use。

Pack6.1k4kFinance
62
OpenSenseNova

sn-da-non-spreadsheet-analysis

Word / PDF / PPT 文档解析与数据分析引擎。覆盖三类文件格式的全量提取、表格数值化、图表理解与跨文档汇总分析。**遇到以下任一情况就主动使用本 skill**:①用户上传或指定了 .docx / .doc / .pdf / .pptx / .ppt 文件并要求分析、提取或统计其中内容;②用户出现触发词:Word分析 / PDF解析 / PPT提取 / 文档分析…

Pack6.1k4kDocuments
62
OpenSenseNova

sn-proactive-agent

安装、启动和使用 Proactive Agent,记录项目进展并在合适时机提醒下一步。

Pack6.1k4kCoding
62
OpenSenseNova

sn-research-report

用于撰写或组织研究报告结构。按读者认知任务(全景/对比/调查/时序)和领域惯例(学术/医疗/法律/政策)选择报告模板。

Pack6.1k4kResearch
61
OpenSenseNova

sn-ppt-story

当前 PPT 任务已由 sn-ppt-entry 建好 DECK_DIR(task_pack.json 与 info_pack.json 已写入)后,必须由本 skill 将 query、全部用户材料与已完成 Research 编排为唯一可编辑的 outline.md 时使用。本 skill 是 entry → 出口(standard / dazzle /…

Pack6.1k4kCoding
61
OpenSenseNova

sn-prepare-citations

用于终稿完成且脚注需要后处理时:去重 [^key] 引用,转换为 [N] 编号,并追加参考文献。

Pack6.1k4kResearch
61
OpenSenseNova

sn-search-image

USE FOR Google-backed image discovery via Serper.dev. Returns image URLs, page URLs, titles, and source domains.

Pack6.1k4kImages & art
58
OpenSenseNova

sn-report-format-discovery

用于用户希望推荐研究成品形式,或最终形式无法从需求中直接判断时。把需求解析为一个简短的 format 字符串,不创建格式文件或 schema。

Pack6.1k4kProduct management

Showing 30 of 84. See the full pack on GitHub.

From the README

How to use SenseNova-Skills

SenseNova-Skills

English | 简体中文

Website Raccoon API Docs SenseNova U1 SenseNova 6.8

The SenseNova model family plugs directly into agent runtimes such as OpenClaw and hermes-agent, with the skills in this repository extending the models with concrete, end-to-end office capabilities.

In this repository each skill lives in its own directory and declares triggers, capabilities, and execution flow through a SKILL.md file, following the Agent Skills convention.

The skills cover image generation & visualization, slide-deck (PPT) generation, Excel data analysis, deep research, code-driven video creation, HTML experiences, team collaboration, and proactive project tracking — usable standalone or composed into end-to-end workflows.

🎨 Want to see what it can do? Check out our sn-infographic Gallery to explore nearly 100 stunning generation cases and steal their prompt designs !

🦝 Available out-of-the-box in Raccoon

The latest SenseNova models and the full Cowork-Skill suite in this repo are bundled into Raccoon, with enterprise-grade security and a zero-setup experience — if you'd rather not provision env, API keys, and runtimes yourself, you can use these capabilities directly through Raccoon. Free trial available — no payment required to get started.

Raccoon now ships a full upgrade across product capability and client experience:

  • Three core office capabilities, strengthened: powered by SenseNova 6.7 Flash + Cowork-Skill, data analysis, PPT generation, and task planning each take a step up — covering the full loop from multi-file cleaning/analysis to formal report decks, industry/competitive research, and investment memos.
  • New: infographic generation: built on the SenseNova U1 model, compresses complex data, long reports, and business insights into dense, structured, visual infographics that are easier to digest and share.
  • New client + local Agent OS: the cloud model handles heavy reasoning and multimodal understanding; the local Agent OS sits next to your files, work context, and personal habits — delivering a more personalized, local, and secure AI-native office experience.
  • Proven at scale: chosen by 15M+ individual users and thousands of enterprise customers.

👉 Try it: xiaohuanxiong.com

How to Use

These skills are designed to run inside an Agent Skills-compatible agent.

This repo documents both the international and mainland China SenseNova API flows. Make sure the docs page, API key, base URL, and model name all come from the same region.

Recommended: let the agent install the skills for you. Hand it the repo URL and ask it to clone and drop the skills into the right directory — for example:

"Please install SenseNova-Skills from https://github.com/OpenSenseNova/SenseNova-Skills into your skills directory."

After it finishes, you may need to manually restart the agent service before the new skills are picked up.

Agent Target directory
OpenClaw ~/.openclaw/skills/
hermes-agent ~/.hermes/skills/
Prefer to install manually?

Clone this repository, then copy the subdirectories under skills/ into the target directory yourself:

git clone https://github.com/OpenSenseNova/SenseNova-Skills.git --depth=1
mkdir -p ~/.openclaw/skills
cp -r SenseNova-Skills/skills/* ~/.openclaw/skills/

For Hermes, swap the target to ~/.hermes/skills/.

Per-category Python dependencies, API keys, and invocation examples are documented in the 📖 Full guide for each section.

Skills List

🎨 Image & Visualization

📖 Full guide: docs/sn-image-generate_en.md (prerequisites, Quick Start, API config, and invocation samples).

Name Label Description
sn-image-doctor Environment Doctor Validates the SenseNova-Skills environment — checks sn-image-base install, Python deps, and required env vars; interactively fills missing values into .env.
sn-image-base Image Base Layer (Tier 0) Low-level tools — text-to-image (sn-image-generate), image editing (sn-image-edit), image recognition (sn-image-recognize), and text optimization (sn-text-optimize) — exposed through a unified sn_agent_runner.py, designed to be called by upper-layer skills.
sn-infographic Infographic Generation (Tier 1) Auto prompt-quality scoring, layout/style selection (87 layouts / 66 styles), multi-round generation with VLM review and quality ranking, producing publication-ready infographics. Supports SenseNova U1.5 Lite, including native 4K output.
sn-image-imitate Image Imitation (Tier 1) Given one reference image and a target content prompt, generates a new image that imitates the reference.
sn-image-resume Resume Image Generation (Tier 1) Given resume information, generates a resume image.

📊 Presentations (PPT)

📖 Full guide: docs/sn-ppt-generate.md (prerequisites, Quick Start, API config, and invocation samples).

Name Label Description
sn-ppt-entry PPT Entry Point Unified entry point for PPT generation. Collects role / audience / scene / page count / mode (standard, dazzle, or creative), parses pdf / docx / md / txt inputs, emits task_pack.json + info_pack.json, and dispatches to the downstream mode.
sn-ppt-story PPT Outline (Story) Mandatory mid-stage between the entry and the exit modes: turns the query, user materials, and completed research into the single editable outline.md; must not be skipped or written by hand.
sn-ppt-standard PPT Standard Mode style spec → outline → asset plan + per-slot images + VLM QA → per-page HTML → per-page review → build present.html; exports PPTX via its own HTML→PPTX exporter.
sn-ppt-dazzle PPT Dynamic Mode Turns a prepared outline.md into a single-file 1280×720 dynamic HTML deck (motion, page transitions, keyboard navigation) for animated/interactive presentations.
sn-ppt-creative PPT Creative Mode One full-page 16:9 PNG per slide generated from a per-page composed prompt; exports PPTX.
sn-ppt-doctor PPT Environment Doctor Checks local rendering/export dependencies (Python/Node Playwright, Chromium, PPTX exporter) and Bundled media config; reports only — never writes .env or modifies the task directory.
sn-ppt-tools Bundled Tool Fallback Provides the fallback (web search, image search, image generation, image download) when the host's native search/image tools are absent or fail; reads SN_PPT_* config from .env.
sn-ppt-workbench PPT Edit Workbench Opens or reuses the AI PPT editing WebUI for an existing HTML deck: preview, inspect, and visually fine-tune in the browser; never regenerates the deck or edits slide files directly.

📈 Data Analysis (DA)

📖 Full guide: docs/sn-data-analysis.md (prerequisites, Quick Start, API config, and invocation samples).

Name Label Description
sn-da-excel-workflow Excel Analysis Orchestration End-to-end Excel pipeline — multi-sheet read, large-file detection (≥10k rows triggers Parquet), cleaning, conditional filtering, cross-sheet aggregation, and Excel/CSV export.
sn-da-image-caption Image Understanding & Data Extraction For image-first inputs — table OCR, chart understanding, screenshot/UI description; parses captions into DataFrames, recreates visualizations, exports Excel/CSV.
sn-da-large-file-analysis High-Performance Large-File Analysis Streaming reads for ≥10k-row Excel datasets (openpyxl read_only + iter_rows), Parquet conversion, memory optimization, chunked processing, large-file writes.

🔬 Deep Research

📖 Full guides: docs/sn-deep-research.md and docs/sn-deepresearch-cli.md (prerequisites, Quick Start, CLI setup, and per-stage invocation).

Name Label Description
sn-deep-research Deep Research Entry Point Mode-aware deep-research orchestrator with parallel research work packages, one-pass quick/normal synthesis, and an auditable heavy workflow, producing final report.md.
sn-deepresearch-cli Deep Research CLI Installs and operates the standalone sensenova-skills-deepresearch CLI, coordinating search, research, monitoring, recovery, and report export through a selected Harness or Agent.
sn-research-report Final Report Writing & Editing Renders the judgment layer into the final report.md; also handles targeted rewrites — restructuring, polishing, table-augmentation — for an existing draft.
sn-report-format-discovery Presentation-Format Discovery Optional standalone format recommendation; sn-deep-research uses a single request-level format string instead of format artifacts.
sn-prepare-citations Citation Rendering Post-processes [^source_id] footnotes into numbered citations and appends references from evidence sources.

📖 Search skills are documented together with deep research: docs/sn-deep-research.md (includes per-platform API keys, invocation, and unified JSON output).

Name Label Description
sn-search-academic Academic Search ArXiv (with section-level HTML reading) / Semantic Scholar (with citation counts) / PubMed (with PMC open-access full text) / Wikipedia, in one aggregated interface.
sn-search-code Developer Search GitHub (repo / code / issue) / Stack Overflow / Hacker News / HuggingFace (models / datasets / spaces), aggregated.
sn-search-social-cn Chinese Social Search Bilibili / Zhihu / Douyin search; some platforms require cookie auth.
sn-search-social-en English Social Search Reddit / Twitter (X) / YouTube search.

🎬 Code-driven Video Creation

📖 Full guide: docs/sn-code-video.md (requirements, setup, rendering, sound, and verification).

Name Label Description
sn-code-video Code Video Creates and revises code-driven MP4 videos with deterministic frame rendering, eight craft guides, optional sound and narration, contact-sheet review, and final-file verification.

🌐 HTML & Web Experiences

📖 Full guide: docs/sn-motion-html.md (continuous-shot stories, media generation, project setup, and browser QA).

Name Label Description
sn-motion-html Motion HTML Storytelling Builds immersive, scroll-driven web stories with a continuous camera journey, consistent stills, Seedance clips, structured content, and responsive browser delivery.
sn-md-to-html-report Markdown → HTML Report Reworks a Markdown report into a self-contained HTML feature page with editorial structure, evidence order, responsive layout, and offline-friendly assets.

🤝 Team Collaboration

📖 Full guide: docs/sn-team-harness.md (self-hosted setup, core concepts, local execution, and security boundaries).

Name Label Description
sn-team-harness Team Harness Explains the self-hosted workspace where people and local Agents share context, projects, work items, resources, and versioned artifacts.

🔔 Proactive Project Tracking

📖 Full guide: docs/sn-proactive-agent.md (installation, Hermes / OpenClaw integration, Web workbench, data layout, and acceptance checks).

Name Label Description
sn-proactive-agent Proactive Agent Tracks long-running project progress, keeps auditable Project / Item / Event records, and presents next-step suggestions in a Web workbench; accepted suggestions resume the original Hermes or OpenClaw session.

Both integrations currently require a model-configured Hermes CLI for background processing. OpenClaw uses a Gateway plugin and does not require the Hermes Connector.

Sample Outputs

🎨 Infographic (sn-infographic)

A few sn-infographic outputs (more in docs/sn-infographic-examples.md).

sn-infographic sample outputs

🧩 Memory price analysis — insight → analysis → presentation → end-to-end workflow

examples/memory-price-end2end-analysis. Starting from a raw quote CSV, the agent profiles fields, normalizes categories and timestamps, then attacks the rally from three angles — overall trend, top movers per category, and the gap between server-grade and consumer-grade SKUs — locating a late-February inflection along the way. Treating those findings as the research question, it switches to deep research: planning per-dimension web searches over supply contraction, AI-server demand, and vendor output discipline, then triaging and cross-checking evidence across sources before committing it to the report. The data and research conclusions are then handed to PPT generation, which lays out a 16-page outline, plans per-slot imagery, renders per-page HTML, runs VLM review, and finally composites screenshots into the PPTX. The result is a clear three-step storyline: prices are rising → here is why → here is what to do. This is the only example that exercises the full data analysis → deep research → PPT chain end-to-end.

📊 Employee performance analysis — data analysis

examples/employee-performance-analysis. The agent reads 10 separate monthly review xlsx files, aligns column schemas across months and joins them into one longitudinal table. From that table it produces aggregate views — monthly average trend, score-distribution boxplots, grade mix change, and a 38-role ranking — and individual views — top performers, needs-attention, and consistently-improving cohorts plus per-employee year trends. The findings are written up with explicit improvement suggestions tied to specific roles and individuals, backed by 8 supporting charts. The same content is delivered as a Word doc (for distribution) and a visualized HTML report (for browsing). The example shows how sn-da-excel-workflow handles "many small spreadsheets that should be one analysis" rather than a single big file.

🔬 Embodied AI industry research — deep research

examples/embodied-ai-deep-research. Given only an industry name, the agent first commits to a research plan — market size, vendor share, financing, cost structure, development roadmap — instead of jumping straight into search. For each dimension it runs targeted web searches, fetches and reads source pages, and extracts both numeric and qualitative evidence; conflicting figures across sources are explicitly reconciled before being trusted. A synthesis stage organizes per-dimension evidence into a traceable, reader-oriented information structure rather than a stack of disconnected bullets. The output is an illustrated report (Markdown + visualized HTML) with 5 dimension-specific charts. The example shows how sn-deep-research turns "go research X" into a structured plan-then-execute loop with traceable evidence.

🎯 Property fee pricing — PPT generation

examples/property-fee-pricing-ppt. The agent takes a free-form brief — topic (property fee pricing), audience (property staff + committee), 26 pages, black-and-white warm style — and first commits to an outline plus a per-page asset plan that conforms to the style spec. Each slide is then built as semantic per-page HTML rather than free-form image generation: copy, layout, illustrations, icons, and any data charts are reasoned about per slot. Imagery is produced or selected per slot and VLM-checked against the page's intent; each rendered page goes through a review pass with optional rewrite for coherence and copy quality. Final pages are screenshotted and composited into the PPTX, with the per-page HTML kept alongside for direct browser preview or re-editing. The example demonstrates sn-ppt-standard style consistency on a long, prose-heavy deck where every slide must obey the same audience and palette constraints.

Third-Party Quick Try

If you want to try a single skill before setting up the full local stack, here are some community / third-party entry points.

These links are maintained outside this repository and are not part of the official SenseNova-Skills support surface. Availability, account requirements, and platform terms may vary by provider.

FAQ

Common setup and runtime questions (400/401 errors, rate limits, PPT timeouts, infographic quality, model names) are answered in docs/faq.md.

Contributing

Feel free to use the skills here as templates for your own OpenClaw skills. The qualities that make a skill good:

  • Clear triggers: state in description exactly when the skill should and should not run, so the agent recognizes it accurately
  • Focused scope: each skill does one thing well; complex workflows compose multiple skills
  • Solid documentation: examples, artifact contracts, edge cases, failure handling
  • Supporting resources: use references/, scripts/, prompts/ to provide additional context

Join the Community

Join our growing community to share feedback, get support, and stay updated on the latest developments. Scan the QR code below to hop into the chat — we'd love to hear from you!

Discord Lark Group

License

MIT — see LICENSE.

Questions

What is OpenSenseNova/SenseNova-Skills?

Modular SenseNova skills for building AI-powered office assistants and productivity workflows

How do I install SenseNova-Skills?

Run "npx skills add OpenSenseNova/SenseNova-Skills" and choose the skills you want. Many packs also document their own install path (for example a Claude Code plugin marketplace) in the README below.

How many skills are in SenseNova-Skills?

84 SKILL.md skills. Alyn lists 30 of them with their own pages.