- 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:
- Verify
.envcontains necessary credentials (WP_URL, LLM provider keys, Scraper keys). - Run
scripts/setup.pyto 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:
- Execute
scripts/daily_worker.py. - 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:
- Execute
scripts/analytics_worker.py. - The worker evaluates Google Search Console data against established age gates.
- 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 acquiringget_chroma_lock()fromsetup.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.pybased on the parsed Pydantic content outline.