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Self Improving Memory Agent

self-improving-agent

alirezarezvani/claude-skills

Analyzes Claude Code auto-memory, promotes stable learnings to CLAUDE.md/.claude/rules, extracts reusable skills, monitors MEMORY.md health, and provides review/promotion/extraction commands to keep project knowledge curated and actionable.

Alexa AI Voice Assistant Integration

sickn33/antigravity-awesome-skills

A comprehensive solution for building advanced, intelligent voice skills for Amazon Alexa. This system transforms standard Alexa devices into ultra-smart assistants by integrating the power of Claude (LLM) as the core brain. It utilizes the full AWS ecosystem, including Lambda, DynamoDB, Polly, and Lex, to enable complex functionalities like smart home control, persistent memory, and natural language understanding.

AI Writing Cleaner

avoid-ai-writing

sickn33/antigravity-awesome-skills

Audits prose for 21 AI-writing patterns, swaps flagged terms via a 43-entry table, rewrites the passage with human phrasing, and runs a second-pass review so content sounds natural before publishing.

Claude Performance Monitor

sickn33/antigravity-awesome-skills

Diagnoses Claude Code and local system slowdowns by checking CPU, RAM, disk, browser usage, and Claude API latency; generates health reports and suggests corrective actions or automated background monitoring for troubleshooting performance complaints.

OpenClaw Phone Calling

davepoon/buildwithclaude

Enables an OpenClaw agent to place managed outbound phone calls for alerts, briefings, reminders, and urgent notifications without Twilio, combining REST-triggered dialing with transcription and TTS so conversations feel like chat.

Advanced LLM Operations

sickn33/antigravity-awesome-skills

LLM-OPS orchestrates production-grade LLM operations, covering RAG, embeddings, vector databases, fine-tuning, prompt engineering, semantic caching, cost estimation, evals, and streaming agents so you can build reliable, scalable AI services.

Task Intelligence Briefing

task-intelligence

sickn33/antigravity-awesome-skills

Coordinates a pre-task intelligence protocol that activates all relevant agents, synthesizes parallel analyses, estimates real execution time, maps probable risks, and produces a contingency-aware plan before executing the user’s request.

Persistent Video Intelligence

seek-and-analyze-video

sickn33/antigravity-awesome-skills

Search, import, and analyze TikTok, YouTube, and Instagram content via Memories.ai LVMM, indexing videos once for repeatable Q&A, summarization, social research, and searchable knowledge-base building backed by MAG.

Autonomous AI Research Orchestration Engine

Orchestra-Research/AI-Research-SKILLs

This skill orchestrates end-to-end autonomous AI research projects using a sophisticated two-loop architecture. It manages the entire research lifecycle, from initial literature review and hypothesis formation to running constrained experiments and synthesizing findings into publishable papers. It acts as a project manager, autonomously driving the process while structuring the workspace and presenting progress to human users.

AI Tool Call Reliability Guardian

tool-use-guardian

sickn33/antigravity-awesome-skills

An advanced reliability wrapper for AI agents that monitors, manages, and recovers from tool call failures. It automatically handles common issues such as truncated JSON responses, API timeouts, rate limits, and mid-chain process breakdowns. By implementing sophisticated failure classification, checkpointing, and learning mechanisms, Guardian ensures complex, multi-step agent workflows remain stable and resilient.

AI Engineering Toolkit

ai-engineering-toolkit

sickn33/antigravity-awesome-skills

Provides six structured AI engineering workflows—from prompt evaluation and context budgeting to RAG architecture, security audits, evaluation harnesses, and product sense coaching—ensuring repeatable, CI/CD-friendly decisions before deployment.

Autonomous Review Loop

auto-review-loop

wanshuiyin/Auto-claude-code-research-in-sleep

Autonomously orchestrates multi-round research reviews via Codex MCP: review, implement fixes, and re-review until the reviewer declares the work ready or the max rounds expire. Logs progress, maintains compact/recoverable state, and optionally adds human checkpoints for iterative improvement requests.

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