Stores durable facts in a categorized, plain-markdown vault on disk, alongside your agent's built-in memory.
Design & media
sn-image-base
Try itBase-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.
What it does
is the base-layer skill (tier 0) of the SenseNova-Skills project and provides three low-level tools:
The skill document
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/completionsinterfaceanthropic-messages: Anthropic Messages/v1/messagesinterface
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/completionsinterfaceanthropic-messages: Anthropic Messages/v1/messagesinterface
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-key)
python scripts/sn_agent_runner.py sn-image-generate \
--prompt "..." \
--api-key "sk-xxx"
# Image recognition (VLM) - minimal call (uses built-in Sensenova defaults)
python scripts/sn_agent_runner.py sn-image-recognize \
--user-prompt "Describe the image" \
--images "path/to/image.png"
# Image recognition (VLM) - override to Anthropic Claude API compatible (messages interface)
python scripts/sn_agent_runner.py sn-image-recognize \
--user-prompt "Describe the image" \
--images "path/to/image.png" \
--api-key "sk-ant-xxx" \
--base-url "https://api.anthropic.com" \
--model "claude-sonnet-4-6" \
--vlm-type "anthropic-messages"
# Text optimization (LLM) - minimal call (uses built-in Sensenova defaults)
python scripts/sn_agent_runner.py sn-text-optimize \
--user-prompt "Optimize the text: ..."
# Text optimization (LLM) - override to Anthropic Claude API compatible (messages interface)
python scripts/sn_agent_runner.py sn-text-optimize \
--user-prompt "Optimize the text: ..." \
--api-key "sk-ant-xxx" \
--base-url "https://api.anthropic.com" \
--model "claude-sonnet-4-6" \
--llm-type "anthropic-messages"
Default Parameter Behavior
Authentication parameters for sn-image-generate have the following default behavior:
| Parameter | Default | Override | Description |
|---|---|---|---|
--base-url | SN_IMAGE_GEN_BASE_URL -> SN_BASE_URL | --base-url "..." | CLI argument has priority |
--api-key | SN_IMAGE_GEN_API_KEY -> SN_API_KEY | --api-key "..." | CLI argument has priority; throws MissingApiKeyError if all values are empty |
sn-image-recognize and sn-text-optimize use priority: CLI argument > command-specific env var > shared SN_CHAT_* env var > global SN_* env var > built-in default.
| Parameter | Built-in Default | Vision Env Var | Text Env Var |
|---|---|---|---|
--api-key | None (must be provided) | SN_VISION_API_KEY -> SN_CHAT_API_KEY -> SN_API_KEY | SN_TEXT_API_KEY -> SN_CHAT_API_KEY -> SN_API_KEY |
--base-url | https://token.sensenova.cn/v1 | SN_VISION_BASE_URL -> SN_CHAT_BASE_URL -> SN_BASE_URL | SN_TEXT_BASE_URL -> SN_CHAT_BASE_URL -> SN_BASE_URL |
--model | sensenova-6.7-flash-lite | SN_VISION_MODEL -> SN_CHAT_MODEL | SN_TEXT_MODEL -> SN_CHAT_MODEL |
--vlm-type / --llm-type | openai-completions | SN_VISION_TYPE -> SN_CHAT_TYPE | SN_TEXT_TYPE -> SN_CHAT_TYPE |
api_key resolution order (high to low): CLI --api-key > command-specific key (SN_VISION_API_KEY/SN_TEXT_API_KEY) > SN_CHAT_API_KEY > SN_API_KEY. If all are unset, MissingApiKeyError is raised.
Only --api-key must be provided via CLI or environment; base URL, model, and interface type have shared chat defaults.
Agent Configuration Integration
The agent can automatically read parameters from openclaw.json without manual input:
| CLI Parameter | openclaw.json Field | Example |
|---|---|---|
--base-url | providers..baseUrl | https://api.anthropic.com |
--llm-type | providers..api | anthropic-messages / openai-completions |
--vlm-type | providers..api | anthropic-messages / openai-completions |
--model | providers..models[].id | claude-sonnet-4-6 |
--api-key | providers..apiKey or env var | sk-cp-... |
Note: --llm-type and --vlm-type share the same providers..api field and are used by LLM and VLM tools respectively.
Mapping between provider.api and interface type:
| api Value | Corresponding --llm-type / --vlm-type | Endpoint Path |
|---|---|---|
anthropic-messages | anthropic-messages | /v1/messages |
openai-completions | openai-completions | /v1/chat/completions |
openai-responses | (future extension) | /responses |
Mapping Between base-url and Interface Type
Different API types have different requirements for base-url format:
| Type | --llm-type / --vlm-type | Recommended base-url | Code Appended Path | Final URL Example |
|---|---|---|---|---|
| LLM | openai-completions | https://token.sensenova.cn/v1 | /chat/completions | https://token.sensenova.cn/v1/chat/completions |
| LLM | anthropic-messages | https://api.anthropic.com/v1 | /messages | https://api.anthropic.com/v1/messages |
| VLM | openai-completions | https://token.sensenova.cn/v1 | /chat/completions | https://token.sensenova.cn/v1/chat/completions |
| VLM | anthropic-messages | https://api.anthropic.com/v1 | /messages | https://api.anthropic.com/v1/messages |
Note:
- Recommended chat base URLs include the provider API version path, for example
/v1. - For compatibility, if the configured chat base URL has no path, the runner appends
/v1/chat/completionsor/v1/messages. - If the configured chat base URL already has a path such as
/v1, the runner appends only/chat/completionsor/messages. - Some providers use versioned paths other than
/v1, such as Gemini's/v1beta/openai.
Output Format
All tools support two output formats:
--output-format text(default): outputs plain text result--output-format json: outputs JSON, includingstatusandelapsed_seconds(runtime in seconds, rounded to 2 decimals)
JSON output for sn-image-recognize and sn-text-optimize also includes model, base_url, and interface_type to verify the effective runtime configuration:
{
"status": "ok",
"result": "...",
"model": "sensenova-6.7-flash-lite",
"base_url": "https://token.sensenova.cn/v1",
"interface_type": "openai-completions",
"elapsed_seconds": 1.23
}
On failure:
{
"status": "failed",
"error": "error message",
"elapsed_seconds": 0.05
}
Input/Output Specification
See references/api_spec.md for details.
Related skills
Generate and edit Draw.io, Mermaid, and Excalidraw diagrams from natural language using a structured JSON spec.
Join a video meeting as an AI bot with voice, avatar, and screenshare across four operating modes.
Find why your productivity system keeps failing, then apply the smallest fix — capacity math, bottleneck routing, durable local notes.
Fetch raw ad creative, app, ranking, and revenue data from AdMapix as structured JSON.
Site audit, content writing, and competitor analysis for organic search rankings.
More from sensenova-skills
Browse all skills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 / 调研报告 / 深度报告 / research / deep research;②请求需要跨多来源取证、多维度对比、交叉验证才能给出可靠结论;③用户要求产出报告、白皮书、行业分析或尽调文档;④话题涉及最新政策/市场/产品/价格/法规,需要系统核查。无核验要求的简单常识问答不使用。模糊或宽泛的"研究/了解一下 X"也优先触发。仅不用于:一句话摘要、已给定单一来源的整理、纯文字润色改写。
Generates professional infographics with various layout types and visual styles. Analyzes content, recommends layout and style, and generates publication-ready infographics. Use when user asks to create "infographic", "信息图", "visual summary", or "可视化".
Open the AI PPT editing WebUI for previously generated SenseNova HTML slides. Use when the user asks to preview, inspect, edit, or open an existing/generated PPT deck in the WebUI/workbench without regenerating slides. Accepts an explicit deck_dir or auto-detects the newest local ppt_decks entry containing HTML pages. Does not run style/outline/page-html/export generation.
多来源深度调研、系统分析、事实核查与完整研究报告交付
从主题策划到 AI 图片、视频和滚动网页的一体化制作
Standard and fast PPT pipeline. All LLM / VLM / T2I calls are wrapped in a single CLI entry (scripts/run_stage.py). The main agent's job is simple: emit ONE shell command per stage, never write loops, never write prompts. Standard mode plans thoroughly with a three-sample deck preview checkpoint (three concatenated deck images plus a preview URL), web research, image search, and user-selected final output format (PPTX or PDF) for polished, delivery-ready presentations. Fast mode builds a complete draft immediately with autonomous decisions, then provides structured refinement suggestions so the user can iterate quickly. Supports AI-generated infographics (U1) for diagrams and flowcharts, web image search (Serper) for real photos, and ECharts for data charts.