/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 only calls backend services and returns results. This skill is not user-facing and is
$ npx -y skills add OpenSenseNova/SenseNova-Skills --skill sn-image-base --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/sn-image-base
Context preview
The summary Claude sees to decide when to auto-load this skill.
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 only calls backend services and returns results. This skill is not user-facing and is
SKILL.md
sn-image-base.SKILL.mdname: sn-image-base
description: |
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 only calls backend services and returns results.
This skill is not user-facing and is intended for upper-layer skills only.
triggers:
- "SenseNova-Skills Image Generation"
- "SenseNova-Skills 图像基础工具"
- "sn 图像基础工具"
- "SenseNova 图像基础工具"
- "SenseNova Image Generation"
- "sn-image-base"
metadata:
project: SenseNova-Skills
tier: 0
category: infrastructure
user_visible: false
sn-image-base
Dependency Installation
pip install -r requirements.txt
Overview
`sn-image-base` is the base-layer skill (tier 0) of the SenseNova-Skills project and provides three low-level tools:
- `sn-image-generate`: image generation (calls text-to-image-no-enhance API)
- `sn-image-recognize`: image recognition (uses VLM to analyze image content)
- `sn-text-optimize`: text optimization (uses LLM to process text)
This skill **does not perform any input preprocessing** and only calls backend services to return results.
Tools List
sn-image-generate
Image generation tool that calls the text-to-image-no-enhance API.
`--prompt` is required; all other parameters are optional:
| Parameter | Type | Default | Description | |------|------|--------|------| | `--prompt` | string | **Required** | Prompt text for image generation | | `--negative-prompt` | string | `""` | Negative prompt | | `--image-size` | string | `2k` | Image size preset (case-insensitive). Recommended: `2k`. `4k` optional, needs model support (sensenova rejects it → `status=failed`). Other values → `status=failed`. | | `--aspect-ratio` | string | `16:9` | Aspect ratio, e.g. `1:1`, `16:9`, `9:16` | | `--seed` | int | `None` | Random seed for reproducible generation | | `--unet-name` | string | `None` | Specify a UNet model name | | `--api-key` | string | `SN_IMAGE_GEN_API_KEY` -> `SN_API_KEY` | API key (CLI argument has priority; `MissingApiKeyError` is raised when all are empty) | | `--base-url` | string | `SN_IMAGE_GEN_BASE_URL` -> `SN_BASE_URL` | API base URL (CLI argument has priority) | | `--poll-interval` | float | `5.0` | Polling interval (seconds) | | `--timeout` | float | `300.0` | Timeout (seconds) | | `--insecure` | flag | `False` | Disable TLS verification | | `--save-path` | Path | Auto-generated | Save path |
sn-image-recognize
Image recognition tool that uses VLM (Vision Language Model) to analyze image content. Supports multiple image inputs.
`--images` and `--user-prompt` (or `--user-prompt-path`) are required. All other parameters use three-level defaults (CLI > env var > built-in default):
| Parameter | Type | Built-in Default | Env Var | Description | |------|------|-----------|---------|------| | `--api-key` | string | No hardcoded default | `SN_VISION_API_KEY` -> `SN_CHAT_API_KEY` -> `SN_API_KEY` | Chat runtime API key; raises `MissingApiKeyError` when all are unset | | `--base-url` | string | `SN_CHAT_BASE_URL` default | `SN_VISION_BASE_URL` -> `SN_CHAT_BASE_URL` -> `SN_BASE_URL` | Vision provider base URL; falls back to shared chat/global provider | | `--model` | string | `sensenova-6.7-flash-lite` | `SN_VISION_MODEL` -> `SN_CHAT_MODEL` | Vision-capable model name | | `--vlm-type` | string | `openai-completions` | `SN_VISION_TYPE` -> `SN_CHAT_TYPE` | Chat protocol type override | | `--user-prompt-path` | string | `None` | - | Local file path, mutually exclusive with `--user-prompt` | | `--system-prompt-path` | string | `None` | - | Local file path, mutually exclusive with `--system-prompt` |
Available values for `--vlm-type`:
- `openai-completions`: OpenAI-compatible `/v1/chat/completions` interface
- `anthropic-messages`: Anthropic Messages `/v1/messages` interface
sn-text-optimize
Text optimization tool that uses LLM (Language Model) to optimize text content. Does not accept image inputs.
`--user-prompt` (or `--user-prompt-path`) is required. All other parameters use three-level defaults (CLI > env var > built-in default):
| Parameter | Type | Built-in Default | Env Var | Description | |------|------|-----------|---------|------| | `--api-key` | string | No hardcoded default | `SN_TEXT_API_KEY` -> `SN_CHAT_API_KEY` -> `SN_API_KEY` | Chat runtime API key; raises `MissingApiKeyError` when all are unset | | `--base-url` | string | `SN_CHAT_BASE_URL` default | `SN_TEXT_BASE_URL` -> `SN_CHAT_BASE_URL` -> `SN_BASE_URL` | Text provider base URL; falls back to shared chat/global provider | | `--model` | string | `sensenova-6.7-flash-lite` | `SN_TEXT_MODEL` -> `SN_CHAT_MODEL` | Text model name | | `--llm-type` | string | `openai-completions` | `SN_TEXT_TYPE` -> `SN_CHAT_TYPE` | Chat protocol type override | | `--user-prompt-path` | string | `None` | - | Local file path, mutually exclusive with `--user-prompt` | | `--system-prompt-path` | string | `None` | - | Local file path, mutually exclusive with `--system-prompt` |
Available values for `--llm-type`:
- `openai-completions`: OpenAI-compatible `/v1/chat/completions` interface
- `anthropic-messages`: Anthropic Messages `/v1/messages` interface
VLM vs LLM
| Tool | Model Type | Image Input | Interface Type Parameter | |------|----------|-----------------|-------------| | `sn-image-recognize` | VLM (Vision Language Model) | Yes, supports multiple images | `--vlm-type` | | `sn-text-optimize` | LLM (Language Model) | No, text only | `--llm-type` |
Usage
All tools are called through the unified `sn_agent_runner.py` entrypoint:
# Image generation (only prompt required; api-key/base-url have defaults)
python scripts/sn_agent_runner.py sn-image-generate \
--prompt "..."
# Image generation (override base-url)
python scripts/sn_agent_runner.py sn-image-generate \
--prompt "..." \
--base-url "https://custom-endpoint.com/v1"
# Image generation (explicitly override api-Read more
name: sn-image-base description: | 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 only calls backend services and returns results. This skill is not user-facing and is intended for upper-layer skills only. triggers: - "SenseNova-Skills Image Generation" - "SenseNova-Skills 图像基础工具" - "sn 图像基础工具" - "SenseNova 图像基础工具" - "SenseNova Image Generation" - "sn-image-base" metadata: project: SenseNova-Skills tier: 0 category: infrastructure user_visible: false
sn-image-base
Dependency Installation
pip install -r requirements.txt
Overview
`sn-image-base` is the base-layer skill (tier 0) of the SenseNova-Skills project and provides three low-level tools:
- `sn-image-generate`: image generation (calls text-to-image-no-enhance API)
- `sn-image-recognize`: image recognition (uses VLM to analyze image content)
- `sn-text-optimize`: text optimization (uses LLM to process text)
This skill **does not perform any input preprocessing** and only calls backend services to return results.
Tools List
sn-image-generate
Image generation tool that calls the text-to-image-no-enhance API.
`--prompt` is required; all other parameters are optional:
| Parameter | Type | Default | Description | |------|------|--------|------| | `--prompt` | string | **Required** | Prompt text for image generation | | `--negative-prompt` | string | `""` | Negative prompt | | `--image-size` | string | `2k` | Image size preset (case-insensitive). Recommended: `2k`. `4k` optional, needs model support (sensenova rejects it → `status=failed`). Other values → `status=failed`. | | `--aspect-ratio` | string | `16:9` | Aspect ratio, e.g. `1:1`, `16:9`, `9:16` | | `--seed` | int | `None` | Random seed for reproducible generation | | `--unet-name` | string | `None` | Specify a UNet model name | | `--api-key` | string | `SN_IMAGE_GEN_API_KEY` -> `SN_API_KEY` | API key (CLI argument has priority; `MissingApiKeyError` is raised when all are empty) | | `--base-url` | string | `SN_IMAGE_GEN_BASE_URL` -> `SN_BASE_URL` | API base URL (CLI argument has priority) | | `--poll-interval` | float | `5.0` | Polling interval (seconds) | | `--timeout` | float | `300.0` | Timeout (seconds) | | `--insecure` | flag | `False` | Disable TLS verification | | `--save-path` | Path | Auto-generated | Save path |
sn-image-recognize
Image recognition tool that uses VLM (Vision Language Model) to analyze image content. Supports multiple image inputs.
`--images` and `--user-prompt` (or `--user-prompt-path`) are required. All other parameters use three-level defaults (CLI > env var > built-in default):
| Parameter | Type | Built-in Default | Env Var | Description | |------|------|-----------|---------|------| | `--api-key` | string | No hardcoded default | `SN_VISION_API_KEY` -> `SN_CHAT_API_KEY` -> `SN_API_KEY` | Chat runtime API key; raises `MissingApiKeyError` when all are unset | | `--base-url` | string | `SN_CHAT_BASE_URL` default | `SN_VISION_BASE_URL` -> `SN_CHAT_BASE_URL` -> `SN_BASE_URL` | Vision provider base URL; falls back to shared chat/global provider | | `--model` | string | `sensenova-6.7-flash-lite` | `SN_VISION_MODEL` -> `SN_CHAT_MODEL` | Vision-capable model name | | `--vlm-type` | string | `openai-completions` | `SN_VISION_TYPE` -> `SN_CHAT_TYPE` | Chat protocol type override | | `--user-prompt-path` | string | `None` | - | Local file path, mutually exclusive with `--user-prompt` | | `--system-prompt-path` | string | `None` | - | Local file path, mutually exclusive with `--system-prompt` |
Available values for `--vlm-type`:
- `openai-completions`: OpenAI-compatible `/v1/chat/completions` interface
- `anthropic-messages`: Anthropic Messages `/v1/messages` interface
sn-text-optimize
Text optimization tool that uses LLM (Language Model) to optimize text content. Does not accept image inputs.
`--user-prompt` (or `--user-prompt-path`) is required. All other parameters use three-level defaults (CLI > env var > built-in default):
| Parameter | Type | Built-in Default | Env Var | Description | |------|------|-----------|---------|------| | `--api-key` | string | No hardcoded default | `SN_TEXT_API_KEY` -> `SN_CHAT_API_KEY` -> `SN_API_KEY` | Chat runtime API key; raises `MissingApiKeyError` when all are unset | | `--base-url` | string | `SN_CHAT_BASE_URL` default | `SN_TEXT_BASE_URL` -> `SN_CHAT_BASE_URL` -> `SN_BASE_URL` | Text provider base URL; falls back to shared chat/global provider | | `--model` | string | `sensenova-6.7-flash-lite` | `SN_TEXT_MODEL` -> `SN_CHAT_MODEL` | Text model name | | `--llm-type` | string | `openai-completions` | `SN_TEXT_TYPE` -> `SN_CHAT_TYPE` | Chat protocol type override | | `--user-prompt-path` | string | `None` | - | Local file path, mutually exclusive with `--user-prompt` | | `--system-prompt-path` | string | `None` | - | Local file path, mutually exclusive with `--system-prompt` |
Available values for `--llm-type`:
- `openai-completions`: OpenAI-compatible `/v1/chat/completions` interface
- `anthropic-messages`: Anthropic Messages `/v1/messages` interface
VLM vs LLM
| Tool | Model Type | Image Input | Interface Type Parameter | |------|----------|-----------------|-------------| | `sn-image-recognize` | VLM (Vision Language Model) | Yes, supports multiple images | `--vlm-type` | | `sn-text-optimize` | LLM (Language Model) | No, text only | `--llm-type` |
Usage
All tools are called through the unified `sn_agent_runner.py` entrypoint:
# Image generation (only prompt required; api-key/base-url have defaults)
python scripts/sn_agent_runner.py sn-image-generate \
--prompt "..."
# Image generation (override base-url)
python scripts/sn_agent_runner.py sn-image-generate \
--prompt "..." \
--base-url "https://custom-endpoint.com/v1"
# Image generation (explicitly override api-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.
Repo: OpenSenseNova/SenseNova-Skills
Other skills on sensenova-skills.
- /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 capability 子 skill。**遇到以下任一情况就主动使用本 skill,不要自行写几行 pandas 就回答**:①用户出现触发词:Excel 分析 / 表格分析 / 数据分析 /
Open skill - /category-coloring
当Excel文件总行数超过1万行时,通过转换为Parquet格式提升读取性能,提取目标指标并计算最大值,最后将结果输出为Excel并对特定行进行高亮标注。
Open skill - /duplicate-value-coloring
对比Excel多表中的特定系数并对异常值进行颜色标记。
Open skill - /outlier-coloring
识别 Excel 中的超限数值与错误单元格并进行高亮标注。
Open skill - /threshold-cell-coloring
根据Excel总行数自动切换Parquet加速读取,计算特定维度的时间序列平均值,并使用openpyxl输出带有条件格式(如低于均值标绿)和自定义样式的分析报告。
Open skill - /top-value-coloring
根据数据规模动态选择处理策略,对多表数据进行合并、统计筛选,并利用 openpyxl 实现关键指标的自动化样式高亮与格式化导出。
Open skill

