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GAN design pipeline: run gan-generator → gan-evaluator in sequence. Loops until evaluator score ≥ 7.0.
Instalar con Codex o Claude Copia este prompt, pégalo en Codex, Claude u otro asistente, y deja que revise la página de la skill y la instale por ti.
Basado en la clasificación ocupacional SOC
Scan installed skills to extract cross-cutting principles and distill them into rules — append, revise, or create new rule files.
Audit all installed OpenClaw skills for quality: content overlap, freshness, and uniqueness. Supports Quick Scan (changed only) and Full Stocktake modes.
Cluster MEMORY.md entries by theme and optionally generate SKILL.md drafts.
Export MEMORY.md to a timestamped markdown file for sharing or backup.
Import memory entries from a markdown export file, merging with MEMORY.md without duplicating.
Show current workspace memory: MEMORY.md contents, pending recalls, and index status.
| name | cmd_gan_design |
| description | GAN design pipeline: run gan-generator → gan-evaluator in sequence. Loops until evaluator score ≥ 7.0. |
| user-invocable | true |
| origin | openclaw-mas |
| argument-hint | <project-path> <design description> |
Run specialist agents in sequence: gan-generator → gan-evaluator.
Include in the task payload:
Execute specialist agents in sequence: gan-generator → gan-evaluator
{
"agentId": "gan-generator",
"sessionKey": "gan-generator",
"task": "<task description with full context from previous step>",
"runTimeoutSeconds": 0
}
Wait for this agent to complete before proceeding.
{
"agentId": "gan-evaluator",
"sessionKey": "gan-evaluator",
"task": "<task description with full context from previous step>",
"runTimeoutSeconds": 0
}
Wait for this agent to complete before proceeding.
Do not spawn the next agent until the current one completes. Do not spawn agents in parallel. After all agents complete, return the final result to the user.