This agent helps Python teams using the Anthropic or OpenAI SDK safely cut LLM spend without risking regressions. With zero code changes, it maps call sites and runs your test scenarios to rank token waste from missed prompt caching or heavy model tiers. It tests fixes in isolated git worktrees, enforcing a strict "do-no-harm" gate that reverts any patch failing to preserve behavior. It delivers a clear savings audit that converts into verified, behavior-preserving code patches upon opt-in.
Generative-engine-optimization grounded in current GEO research: answer-first rewrites, entity & schema, citable phrasing, Reddit/community strategy and a 30-day AI-visibility plan.
Hands-on prompt engineering and LLM evaluation. Built around a diagnose-then-ship loop: forensic transcript critique ▎ that names the exact failure mode, paired with a fixer that produces complete, deployment-ready rewrites — not ▎ vague advice.
Performs a comprehensive, actionable SEO (Search Engine Optimization), AEO (Answer Engine Optimization), and GEO (Generative Engine Optimization) audit of any website URL. Analyzes technical SEO foundations, on-page factors, E-E-A-T signals, content structure for AI discoverability, schema markup, Core Web Vitals, and cross-web entity strength. Returns a structured, prioritized audit report with clear, immediate action items.
AI tool that optimizes product catalogs for marketplace listings: compliant titles, bullets, backend search terms, fact-locked claims, gap flags, and prioritization — without inventing specs or market data.
"An advanced e-commerce assistant that transforms raw product features into high-converting, SEO-optimized descriptions for Shopify, Amazon, and Etsy."
This is the scoring reference the agent uses to turn raw crawl/API data into prioritized findings. Keep this file as the single source of truth — update it whenever a real audit reveals a false positive or a missing check. Scope covered: Crawlability & Indexation, Performance (Core Web Vitals), Structure & Markup. (Mobile/Architecture can be added in a later version.)
Expert AI investor that evaluates startup pitch decks like a seasoned VC. Scores 9 criteria: Problem, Solution, Market, Business Model, Traction, Team, Financials, Competitive Edge, Market Timing. Provides strengths, weaknesses, tough investor questions, and specific improvements. Works for any industry, stage, and global market.
Scholar Evaluation from affaan-m’s ECC project. Use it to review research papers, proposals, literature reviews, thesis chapters, and other academic work with a structured 1–5 rubric. Evaluate research questions, literature, methodology, evidence, analysis, results, limitations, writing, and citations, then return clear scores, critical issues, revision priorities, and evidence checks.