An AI image analysis and structured-prompting studio.

(: SMILE! The positive prompt language for structured prompt engineering — used for complex prompts, multi-turn pipelines, agentic engineering. Modular & maintainable prompts for powerful Large Language Model responses.

SANCTIS is a cognitive architecture that gives LLMs structured tools to organize their own reasoning, maintain long-horizon coherence, and reduce drift. It installs stable thinking patterns that emerge more powerfully the longer the model runs.

Structured Prompts Improve Evaluation of Language Models

Vine makes accessing AI simpler and more efficient

LeerPlan: AI-Powered Academic Planner LeerPlan streamlines academic scheduling by leveraging Large Language Models. Users upload course syllabuses as PDFs, and LeerPlan automatically generates comprehensive course outlines.

Object-Oriented Prompt Design (OOPD): オブジェクト指向型汎用プロンプト用語定義 (Object-Oriented Terminology for Prompt Design)

Structured Expert Prompting (SEP) — a methodology and 5-file deployment scaffold for building production-ready AI expert personas with built-in verification, forensic analysis, and self-improvement.

🪱 An opinionated, structured vibe-coding starter kit for Claude Code & GitHub Copilot. AI agents, shared context, slash commands, prompt engineering, and local-first issue tracking. Stop blind prompting. Start building with structure.

Structured prompting convention to optimize reasoning precision, execution consistency, and token efficiency

Editorial AI · 直笔 — A Claude Skill for serious writers. Skeleton-first writing, anti-fabrication, diagnosis+prescription, word count discipline. Built for journalists, analysts, PR teams, B2B writers.

A modular prompt architecture for LLM behavior control. YAML-based framework for persona consistency, memory management, and attention guidance across extended AI conversations.

Enter the chamber. Face the gators. Earn the truth.

Structured Markdown Driven Development skills for Claude Code. Plan projects as prose markdown before writing a line of code, then build component-by-component with atomic, parallel-safe sub-agents.

LLM-augmented geodemographic classification of Indian districts using NFHS-5 dataset

Visual Archetype Analysis of Geodemographic Clusters using Vision Language Models

LLM-powered tool for structured information extraction with digestible chunks and guided follow-ups to minimize user effort.

🧠 Enhance Claude Code's capabilities with persistent working memory for better context and multi-instance coordination in large codebases.

🧬 Build consistent AI personalities with the Kotodama Framework, ensuring engaging, reliable interactions throughout your conversations.