Modular SenseNova skills for building AI-powered office assistants and productivity workflows
# Add to your Claude Code skills
git clone https://github.com/OpenSenseNova/SenseNova-SkillsGuides for using ai agents skills like SenseNova-Skills.
Last scanned: 5/15/2026
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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, and deep research — 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:
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These skills are designed to run inside an Agent Skills-compatible agent.
INSTALL.md.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 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. |
| 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 / scenario / page count / mode (creative or standard), parses uploaded pdf / docx / md / txt, emits task_pack.json + info_pack.json, and dispatches to the chosen mode. |
| sn-ppt-doctor | PPT Environment Doctor | Environment check for the PPT pipeline — validates sn-image-base, API keys, the Node runtime, and optional deps; writes missing required vars into .env. |
| sn-ppt-creative | PPT Creative Mode | One full-page 16:9 PNG per slide, generated via sn-image-generate with a per-page composed prompt. |
| sn-ppt-standard | PPT Standard Mode | style_spec → outline → asset plan + per-slot images + VLM QC → per-page HTML → per-page review (with optional rewrite) → aggregated review.md → PPTX export. |
📖 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](skills/sn-da-image-caption/SKILL.m