Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
SAA Agent
Enables AI agents to generate images using the Character Select Stand Alone App (SAA) image generation backend via command-line interface.
skill openclawclawhub Free
Enables AI agents to generate images using the Character Select Stand Alone App (SAA) image generation backend via command-line interface.
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- README_HUMAN.md, saa-agent.py, SKILL.md
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Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.1
Provenance
- Publisher
- mirabarukaso
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Documentation
SAA CLI Tool
A command-line interface for interacting with Character Select Stand Alone App (SAA) via WebSocket connections. Supports both ComfyUI and WebUI backends for AI image generation.
Prerequisites
CRITICAL: Before invoking this tool, confirm with the user that: The SAA backend is running, and version is above 2.4.0 The SAAC (SAA Client) feature is enabled The WebSocket address is available Some Mac users uses python3 instead of python to invoke Python 3.x For SAA setup details, let your owner visit the project repository.
Basic Usage
The tool requires minimal parameters to function. The examples below demonstrate the standard usage pattern:
Minimal Command With Model Selection (Recommended for Most Cases)
python saa-agent.py \ --ws-address "user_provided_ws_address" \ --model "waiIllustriousSDXL_v160.safetensors" \ --positive "your detailed prompt here" \ --negative "low quality, blurry, bad anatomy"
Regional Prompting (Split Composition)
python saa-agent.py \ --ws-address "user_provided_ws_address" \ --model "waiIllustriousSDXL_v160.safetensors" \ --regional \ --positive-left "1girl, warrior, red armor" \ --positive-right "1boy, mage, blue robes"
More Examples
Get more usage examples and detailed parameter explanations: python saa-agent.py python saa-agent.py --help
Required
--ws-address: WebSocket address (obtain from user) --positive: Main prompt OR use --regional mode with --positive-left and --positive-right
Commonly Modified
--model: Change the checkpoint model (default: waiIllustriousSDXL_v160.safetensors) --negative: Specify unwanted elements --width / --height: Image dimensions (defaults: 1024x1360) --steps: Sampling steps (default: 28) --seed: Set specific seed or -1 for random
Advanced (Use Sparingly)
--cfg: CFG scale (default: 7.0) --sampler: Sampling algorithm (default: euler_ancestral) --scheduler: Scheduler type (default: normal)
HiResFix Warning
DO NOT use --hifix unless specifically requested by the user. HiResFix significantly increases generation time and requires substantial GPU resources. Only enable if: User explicitly requests high-resolution upscaling User confirms their GPU can handle the additional load
Backend Busy State
If the generation returns either of these errors: Error: WebUI is busy, cannot run new generation, please try again later. Error: ComfyUI is busy, cannot run new generation, please try again later. Actions to take: DO NOT automatically retry the generation Inform the user: "The SAA backend is currently busy. This could mean another process is generating an image, or the backend is locked from a previous error." Advise: "Please wait 20-60 seconds before trying again." Let the user manually retry DO NOT chain multiple retry attempts as this can worsen backend congestion.
Skeleton Key Usage
The --skeleton-key parameter forcefully unlocks the backend's atomic lock. When to use: User confirms no other processes are using the backend Backend appears stuck despite waiting User explicitly requests unlocking How to use: python saa-agent.py \ --ws-address "user_provided_ws_address" \ --skeleton-key \ --positive "test prompt" Rules: ALWAYS ask for user confirmation before using --skeleton-key ONLY use it once per user request Explain to the user that this forcefully terminates any locks Example conversation: AI: "The backend appears to be locked. Would you like me to use the skeleton key to force unlock it? This will terminate any existing locks." User: "Yes, please unlock it." AI: [proceeds to run command with --skeleton-key]
Parameter Defaults
When in doubt, rely on these defaults - they work well for most cases: Model: waiIllustriousSDXL_v160.safetensors Dimensions: 1024x1360 CFG: 7.0 Steps: 28 Sampler: euler_ancestral Scheduler: normal Seed: -1 (random)
Output Handling
By default, images are saved to generated_image.png. You can specify a custom output path: --output "custom_filename.png" For programmatic handling, use base64 output: --base64 This outputs base64-encoded image data(huge!!!) to stdout instead of saving a file.
Example Workflow
User requests: "Generate an anime girl with long blue hair" AI executes: python saa-agent.py \ --ws-address "user_ws_address" \ --positive "1girl, long hair, blue hair, anime style, detailed" \ --negative "low quality, blurry, bad anatomy" If backend busy error occurs: Inform user Wait for user to retry (don't auto-retry) If success: Confirm image was generated Provide file path if relevant
Common Pitfalls to Avoid
Don't use --hifix unless explicitly requested Don't auto-retry on backend busy errors Don't use --skeleton-key without user permission Don't add excessive parameters - unless explicitly requested, the defaults are well-tuned Don't assume backend is ready - always confirm with user first
Error Codes
Exit code 0: Success Exit code 1: Connection error (check backend is running) Exit code 2: Authentication error (check credentials) Exit code 3: Generation error (check parameters) Exit code 4: Timeout (backend may be overloaded) Exit code 5: Invalid parameters (check command syntax)
Best Practices
Start with minimal parameters with model selection if needed Ask user for WebSocket address on first use Handle busy states gracefully - don't spam retries Use --verbose flag when debugging issues Respect the skeleton key - it's a powerful override tool
AI Agent Guidelines for This Skill
These rules help maintain appropriate transparency and user control when executing generation tasks. Command Execution & User Notification By default, execute the command directly without asking for confirmation. Show the full command and ask for approval only when: The user explicitly requests to review it first The operation involves sensitive or high-impact parameters The agent judges that showing the command is prudent in context Example (when disclosure is needed): python3 saa-agent.py --ws-address "wss://..." --username "..." --password "..." --positive "[prompt]" --negative "[prompt]" --output "[path]" [--verbose] --verbose Flag Not used by default Add automatically or recommend when: Task fails and debugging is needed User specifically asks for detailed logs or seed Result Reporting After completion, provide a short summary to the user by default, including: Success/failure status Positive & negative prompts (or meaningful summary) Seed (if available) Output path Example: Generation completed β’ Positive: [...] β’ Negative: [...] β’ Seed: 123456789 β’ Output: [path] Skip detailed reporting only if the user has clearly requested silent / minimal feedback. Always report errors, even in silent mode. Error Handling On failure: consider one retry with --verbose to capture diagnostic information Communicate the main error cause clearly Do not perform unlimited retries; defer to user after one attempt if needed
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
2 Docs1 Scripts
- SKILL.md
- README_HUMAN.md
- saa-agent.py