Agent Skills Hub

llm-integration

A toolkit for building robust LLM integrations: API patterns, streaming, function calling, RAG pipelines, and cost-effective model routing.

lambda

Manage AWS Lambda serverless functions: deploy code, configure event triggers, debug invocations, optimize cold starts, and maintain layers.

find-bugs

Perform automated security audits, bug detection, and code quality assessments on local branch diffs using a structured, checklist-driven verification process.

swift-patterns

Expert SwiftUI assistant for reviewing, refactoring, and building high-performance, testable, and modern iOS applications using Apple's best practices.

constant-time-analysis

Detects timing side-channel vulnerabilities in cryptographic code through static and dynamic analysis across multiple programming languages.

MLOps Industrialization

A framework to transform experimental ML prototypes into robust, production-ready Python packages using src layout, hybrid architecture, and strict configuration management.

training-data-curation

Guidelines for curating high-quality datasets for LLM post-training (SFT/DPO/RLHF), covering data formats, quality filtering, and collection strategies.

inno-prepare-resources

Automates research resource preparation by loading instances, searching GitHub for codebases, building dataset descriptions, and downloading arXiv papers.

performance-testing

Profiles application performance using k6, Artillery, or JMeter to measure latency, throughput, and error rates. Ideal for planning load, stress, and soak tests to identify bottlenecks.

testing-strategies

Implement robust software testing strategies, including unit, integration, and E2E tests, mocking frameworks, TDD patterns, and best practices for high-quality, reliable code across any stack.

ci

Automated CI/CD incident response, failure analysis, and remediation for GitHub Actions pipelines. Resolves build and test failures with safety guardrails.

basic-usage

Essential guide to llmemory for document storage and search: installation, database setup with pgvector, document ingestion, hybrid/semantic retrieval, and building RAG systems with multi-tenant support.