Autonomous AEO and SEO content generation and optimization engine for scaling business operations. Use when Codex needs to run end-to-end programmatic SEO wo...
--- name: execute-openclaw-pipeline description: Autonomous AEO and SEO content generation and optimization engine for scaling business operations. Use when Codex needs to run end-to-end programmatic SEO workflows, including semantic keyword generation, multi-tiered competitor scraping, dynamic JSON-LD schema generation, and direct WordPress publishing. Also use this skill to trigger the analytics worker for detecting and repairing CTR decay on existing posts. --- # OpenClaw Pipeline Execution ## Initial Setup and Configuration Before running the pipeline, ensure the environment is correctly configured: 1. Verify `.env` contains necessary credentials (WP_URL, LLM provider keys, Scraper keys). 2. Run `scripts/setup.py` to initialize the SQLite database (`openclaw.db`) and ChromaDB vector storage. ## Executing the Daily Worker (Content Generation) To generate and publish new content for scaling operations: 1. Execute `scripts/daily_worker.py`. 2. The pipeline handles: - Semantic query generation based on `TARGET_NICHE`. - Competitor scraping via the waterfall method (Playwright, Firecrawl, Jina). - Content generation using the designated LLM. - Semantic internal link injection. - Direct publication to WordPress. ## Executing the Analytics Worker (Content Optimization) To optimize existing content experiencing CTR decay: 1. Execute `scripts/analytics_worker.py`. 2. The worker evaluates Google Search Console data against established age gates. 3. Eligible posts are updated via the WordPress REST API, and ChromaDB vector embeddings are re-synced. ## Critical Architectural Constraints - **Concurrency:** ChromaDB writes are serialized via `filelock`. Do not attempt to write to ChromaDB concurrently without acquiring `get_chroma_lock()` from `setup.py`. - **Scraping Fallbacks:** If Tier 1-5 scrapers fail, the pipeline falls back gracefully to LLM grounded search synthesis (Tier 6). Do not halt execution if competitor scraping fails. - **Schema Generation:** JSON-LD schema is dynamically constructed via `schema_engine.py` based on the parsed Pydantic content outline.
don't have the plugin yet? install it then click "run inline in claude" again.