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Batch Extraction

batch-extraction

Extract text and data from many files at once with shared config, per-file overrides, bounded parallelism, and error recovery. Supports PDFs, DOCX, XLSX, and more, with JSON or text output for LLM ingestion.

BDI Mental State Modeling

bdi-mental-states

sickn33/agentic-awesome-skills

This skill enables modeling agent mental states using BDI architecture. It transforms RDF context into beliefs, desires, and intentions, supporting cognitive reasoning and explainability in multi-agent systems. It facilitates formal cognitive structures for LLMs and tracks temporal evolution of mental states through ontology patterns.

Cross-Version Binary Symbol Migration

sickn33/agentic-awesome-skills

Migrates symbols and annotations across binary versions using BinDiff-style workflows: compares disassembly and pseudocode with an LLM, then applies YAML mapping results to the new IDB.

BlockRun AI Provider Integration

sickn33/agentic-awesome-skills

BlockRun integrates Claude Code with external AI providers via x402 micropayments, enabling image generation, real-time X search, and second-opinion LLM calls with wallet-based budget control.

BullMQ Job Queue Specialist

bullmq-specialist

sickn33/agentic-awesome-skills

Expert guidance for building reliable Redis-backed job queues with BullMQ in Node.js/TypeScript, covering scheduling, flows, rate limiting, monitoring, and graceful shutdown.

Text Chunking for LLM

Guide for splitting extracted text into chunks for LLM context windows or RAG ingestion. Covers chunk size, overlap, markdown/yaml/semantic chunkers, tokenizer-based sizing, and the standalone chunk command.

Clean Code Review Guard

clean-code-guard

sickn33/agentic-awesome-skills

This skill reviews generated or changed production code against Clean Code principles like SOLID, DRY, and KISS. It checks for LLM-specific failure modes to ensure code quality before shipping. It operates in three modes: guard-pass after generation, live during writing, and review for auditing. It helps AI agents avoid systematic errors and maintain high standards without replacing project linters.

Cohesivity Backend Infrastructure

sickn33/agentic-awesome-skills

Cohesivity provides headless backend services for AI agents via a single HTTP API, including hosting, databases, storage, and LLM access. It supports ephemeral tenants with 72-hour expiration, requiring user approval for new backends. Ideal for bootstrapping new apps or adding services mid-build without vendor consoles.

LLM Context Window Management

context-window-management

sickn33/agentic-awesome-skills

Strategies for managing LLM context windows: tiered routing, summarization, trimming, token counting, and prompt placement to avoid context rot in multi-turn AI applications.

LLM Conversation Memory

conversation-memory

sickn33/agentic-awesome-skills

Provides tiered persistent memory patterns for LLM conversations, including short-term, long-term, entity memory, storage, retrieval, and consolidation.

Daily Pipecat Realtime AI Reference

sickn33/agentic-awesome-skills

Reference for building real-time voice and multimodal AI applications with Daily and Pipecat transports, covering pipelines, STT, TTS, LLM integration, tool calling, context management, and turn detection.

Persistent Codebase Structure Map

data-structure-protocol

sickn33/agentic-awesome-skills

Provides LLM coding agents with a persistent graph of code entities, imports, public APIs, and dependency reasons, enabling navigation, refactoring, and impact analysis without rereading the whole repository.

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