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 intended for upper-layer skills only.
npx skills add OpenSenseNova/SenseNova-Skills --skill sn-image-base --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# sn-image-base ## Dependency Installation ```bash 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` |
- Dependency Installation
- Overview
- Tools List
- sn-image-generate
- sn-image-recognize
- sn-text-optimize
- VLM vs LLM
- Usage
- Default Parameter Behavior
- Agent Configuration Integration
- Mapping Between base-url and Interface Type
- Output Format
- Input/Output Specification
pip install -r requirements.txt Image generation (only prompt required; api-key/base-url have defaults) python scripts/sn_agent_runner.py sn-image-generate \ Image generation (override base-url) Image generation (explicitly override api-key) Image recognition (VLM) - minimal call (uses built-in Sensenova defaults) python scripts/sn_agent_runner.py sn-image-recognize \ Image recognition (VLM) - override to Anthropic Claude API compatible (messages interface) Text optimization (LLM) - minimal call (uses built-in Sensenova defaults) python scripts/sn_agent_runner.py sn-text-optimize \
What does the sn-image-base skill do?
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.
How do I install it?
Run `npx skills add OpenSenseNova/SenseNova-Skills --skill sn-image-base --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From OpenSenseNova/SenseNova-Skills, a repository with 4,855 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.