pcircle-ai-toonify-mcp

Knowledge patches and plugins for Claude covering recent language and framework updates. Fills training data gaps.

200 skills

Guidance on building Retrieval-Augmented Generation systems that combine large language models with document retrieval. Enables AI agents to reference external knowledge bases and provide grounded responses.

184 skills

Token efficiency optimization techniques and utilities for Claude. Helps reduce token consumption in AI workflows.

33 skills · 76 commands

Mental health and wellness analysis tool that identifies psychological patterns, assesses health status, and provides personalized recommendations integrated with sleep, exercise, and nutrition data.

19 skills · 59 commands

PUA is a framework for building and managing AI agent prompts and behaviors. Supports multilingual prompt engineering and agent configuration.

29 skills · 22 commands · 7 agents · hooks

Integrates Gemini image processing with Claude for visual analysis and generation tasks. Enables multimodal image workflows.

50 skills · 6 commands

Persistent memory for Claude Code: the next session starts where the last one left off.

29 skills · 1 MCP server · hooks

Skill: add headroom-ai compress() to a Python or TypeScript app to cut LLM input tokens (tool outputs, logs, JSON, chat history). No API key.

1 skill

Continuous memory for Claude Code. Extracts, summarizes, and compresses conversations into tiered daily logs. Claude remembers what you did yesterday.

Persistent memory for AI coding agents -- captures tool usage, compresses via LLM, injects context into future sessions

17 skills · 1 MCP server · hooks

Ultra-compressed communication mode. Cuts token usage 20-50% (75% upper bound) by dropping filler, articles, pleasantries, and hedging while keeping full technical accuracy. Derived from Matt Pocock's MIT-licensed caveman with: (1) 3 stdlib Python tools (deterministic compressor, token-savings estimator with $/Mtok cost extrapolation, lint that detects banned vocab with code-block + exception-zone whitelisting), (2) 3 references citing 7-8 sources (compression principles, when caveman backfires, companion tooling), (3) cs-caveman-mode persona agent + /cs-caveman slash command. Matt's persistence rules + auto-clarity exception preserved verbatim per MIT.

1 skill · 1 command · 1 agent

Comprehensive context engineering and harness engineering skills for production-grade AI agent systems: fundamentals, degradation patterns, compression, optimization, self-managed context (model-controlled live context editing), multi-agent coordination, long-horizon prompting (pseudo-formal task briefs for long-running and parallel agents), memory systems, tool design, filesystem context, hosted agents, evaluation, autonomous harnesses, self-improvement loops (RSI, meta-harnesses, evolutionary scaffold search), latent briefing (KV cache sharing between agents), project development, and cognitive architecture. Ships with a researcher operating system (rubrics, mechanism registry, claim provenance, run state machine, adversarial benchmarks, continuous loop).

19 skills