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.
$ npx -y skills add OpenSenseNova/SenseNova-Skills --agent claude-code
Repo: OpenSenseNova/SenseNova-Skills
What's inside
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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, 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 !
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:
👉 Try it: xiaohuanxiong.com
These skills are designed to run inside an Agent Skills-compatible agent.
https://token.sensenova.ai/v1
Mainland China: platform.sensenova.cn/token-plan, Base URL https://token.sensenova.cn/v1INSTALL.md.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/ |
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.
📖 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. |
📖 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. |
📖 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. |
FAQ
sensenova-skills is a Claude Code plugin with 83 hand-picked skills for productivity work, indexed on Flowy. Install it with the command on its page. It includes sn-da-excel-workflow, category-coloring, duplicate-value-coloring. Its skills do not fire on their own yet. Request auto-invocation to have Flowy route them as you prompt. Free and open source.
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