optimizer▌

Analyze a draft prompt, critique it, match it to ECC ecosystem components, and output a complete optimized prompt the user can paste and run.

Analyzes markdown files and suggests token-reduction optimizations while preserving clarity. \n \n Counts tokens using a 4-character-per-token approximation and identifies token-wasting patterns including emojis, verbosity, duplication, and oversized code blocks \n Generates a detailed suggestions table showing issue location, description, recommended fix, and estimated token savings \n Targets SKILL.md files for under 500 tokens and reference files for under 1000 tokens \n Provides recommendati

Optimize LinkedIn profiles for recruiter visibility, searchability, and job opportunity attraction. \n \n Provides section-by-section optimization guidance covering headline, About section, Experience, Skills, and Featured content with specific formulas and examples \n Includes keyword strategy for recruiter searches, profile completeness checklist, and recruiter visibility settings configuration \n Explains key differences between LinkedIn and resume formats, with structured approach to syncing

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Specialized in enhancing script performance, user experience, and visual presentation on TradingView.

You are a meta tag optimization specialist creating compelling metadata within best practice guidelines.

Resume optimization for Applicant Tracking Systems with keyword matching and compatibility analysis. \n \n Parses resumes for ATS compatibility, identifies formatting issues (tables, headers/footers, non-standard fonts), and flags file format problems that break automated screening \n Extracts and analyzes keywords from job descriptions across hard skills, soft skills, and industry terms, then calculates match scores between resume and posting \n Provides structured compatibility reports with sp

Implements the NOWAIT technique from the paper "Wait, We Don't Need to 'Wait'! Removing Thinking Tokens Improves Reasoning Efficiency" (Wang et al., 2025).

Build touch-optimized, performant mobile experiences with proper viewport handling and responsive patterns.

Analyze and rewrite tweets to maximize reach using Twitter's open-source recommendation algorithms. \n \n Applies Real-graph, SimClusters, TwHIN, and Tweepcred models to identify optimization opportunities and explain algorithmic ranking decisions \n Identifies engagement signals (likes, replies, retweets, bookmarks) and negative signals (blocks, reports, mutes) that affect tweet distribution \n Rewrites tweets to trigger specific engagement patterns, target community resonance, and strengthen t