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from SEOBuild Onpage
A full workflow for generating SEO-optimised pages designed to rank and be cited by LLMs, using live SERP research, chunk architecture, and quality gates.
Provides a complete framework and playbook for research-driven content creation: runs competitive SERP research, structures pages into 500-token chunks optimized for AI retrieval, enforces quality gates (Reddit Test, Information Gain), and generates tributary drafts for off-site corroboration. Includes scripts for research and tributary generation.
Use when creating or rewriting pages that must rank in modern AI-influenced SERPs—commercial/local/comparative pages where entity signals, structured data, and provenance matter. Also used when integrating upstream research (DataForSEO/Ahrefs/SEMRush/GSC) into content briefs.
Designed for agents that can run Python scripts and shell commands (OpenClaw/Claude Code/Copilot/Gemini CLI). Integrates with MCP tools when available.
Comprehensive SEO content optimization framework (~75KB SKILL.md) covering on-page SEO, LLM/AEO citation strategy, 500-token chunk architecture, Tributary Trust Protocol for off-page entity building, and a 48-point quality checklist. No bundled scripts (0 scripts found). The skill references external scripts (research.py, gsc_pull.py, tributary_gen.py) and reference files that are not included in the skill package, making it partially non-functional out of the box. Security is clean — no hardcoded credentials, no destructive commands, no telemetry, and respects user approval for config changes.
Well-crafted SEO framework with genuine insights (500-token chunk architecture, QDD vulnerability analysis, Tributary Trust Protocol). The 48-point quality checklist is thorough. Main weakness is architectural: the skill package doesn't include the scripts or references it depends on, and the main SKILL.md is monolithic rather than using progressive disclosure. Security is excellent — all API keys via env vars, explicit user approval for config changes, no destructive patterns.
arxiv2md
Convert arXiv papers into clean, LLM-ready Markdown via a REST API or CLI for fast reading, summarization, and downstream processing.
Scite Database (Smart Citations)
Query Scite.ai Smart Citations by DOI to report supporting, contrasting, and mentioning citation counts and help assess a paper's reliability.
Writing Implementation Plans
Generate detailed, engineer-ready implementation plans from design docs: file paths, step-by-step tasks, tests, and verification instructions.
Humanize AI Text
Rewrite AI-generated text into more natural, human-like prose using the HumanizerAI API, with before/after scores and credit tracking.
NotebookLM Research Agent
End-to-end research-to-content pipeline: ingest sources into Google NotebookLM, run deep cited research, generate downloadable artifacts, and produce polished c
AI News Daily
Generate a structured, bilingual daily briefing of the latest AI industry news, model updates, papers, and open-source tools with in-depth technical analysis an
ToolUniverse Gateway
Unified agent gateway to 1000+ scientific tools (bioinformatics, drug discovery, genomics) via Harvard's ToolUniverse, returning JSON for downstream workflows.
Research Information Lookup
Find and synthesize current research and academic papers with automatic backend routing (Parallel Chat API or Perplexity) and structured citations.