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Claude API Patterns

affaan-m/everything-claude-code

Documented best practices for building applications with Anthropic Claude via Python and TypeScript SDKs, covering messaging, streaming, tools, vision, reasoning, caching, batching, and Agent workflows to optimize prompts, tokens, and cost.

Multisource Evidence Research

affaan-m/everything-claude-code

Leverages firecrawl and exa MCP tools to run focused multi-source searches, scrape key documents, and synthesize citation-backed reports whenever a user needs thorough evidence-based research on any topic.

Parallel Agent Workflows

affaan-m/everything-claude-code

Coordinate multiple AI agents concurrently via dmux’s tmux pane manager, running Claude Code, Codex, OpenCode and other tools in parallel tracks for research, implementation, testing, review, or multi-role coding tasks.

Exa Neural Search

affaan-m/everything-claude-code

Coordinates Exa MCP-driven web_search_exa and get_code_context_exa calls for up-to-date web results, code snippets, and company or people intel whenever the user requests research, competitive analysis, or development context.

Fal AI Media Studio

affaan-m/everything-claude-code

Fal.ai Media Studio via MCP unifies image, video, and audio generation using Nano Banana, Seedance, Kling, Veo 3, CSM-1B, and ThinkSound models, enabling prompt-driven drafts, high-fidelity renders, and multimodal content for creative workflows.

Structured Output Extraction

llm-structured-output

sickn33/antigravity-awesome-skills

Teaches how to steer OpenAI, Anthropic, Google, and local LLMs into emitting validated JSON/enums by defining strict schemas, prompting for data extraction, handling validation failures, and building retry/logging pipelines.

Prompt Optimization Assistant

prompt-optimizer

affaan-m/everything-claude-code

Analyzes draft prompts, identifies intent and missing pieces, matches ECC components, and outputs a ready-to-use optimized prompt while explicitly advising against taking implementation actions.

Root Cause Analyst

analyze-project

sickn33/antigravity-awesome-skills

Analyzes Antigravity AI coding sessions to classify scope deltas, rework patterns, root causes, and recommend prompt or process improvements backed by evidence.

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.

RecallMax Memory Engine

sickn33/antigravity-awesome-skills

RecallMax supercharges AI agents by injecting 500K–1M clean tokens, adaptively summarizing each turn, compressing history, and verifying facts so long conversations stay coherent without hallucinations.

Tool Use Reliability Guard

tool-use-guardian

sickn33/antigravity-awesome-skills

Intelligent reliability wrapper that monitors agent tool calls, retries failures, heals malformed responses, and checkpoint-resumes interrupted chains so your workflows recover automatically without hand-coded retry logic.

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.

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