swe-cli-skills
Expert CLI guides for AI agents, featuring senior engineer workflows, safety guardrails, and operational patterns for cloud, IaC, containers, databases, and dev tools.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
559 skills found
Expert CLI guides for AI agents, featuring senior engineer workflows, safety guardrails, and operational patterns for cloud, IaC, containers, databases, and dev tools.
Enforces disciplined Test-Driven Development (TDD) by requiring a failing test before implementation, ensuring code reliability and preventing premature over-engineering.
Act as a skeptical technical recruiter to evaluate daily.dev Recruiter features. Review UI/UX, code, and workflows through the lens of a hiring platform built for high-quality developer-recruiter matching.
Research agent for Nia: index/search remote codebases, docs, and packages. Optimizes AI context by prioritizing full source indexing over web fetches to reduce hallucinations.
An autonomous UI implementation agent that converts Figma designs into pixel-perfect code using Figma MCP and browser-based refinement.
Comprehensive code quality validation for LibrAgent, covering TypeScript frontend and Rust/Tauri backend via automated linting, formatting, type checking, and build verification.
Specialized data engineering agent for designing ETL/ELT pipelines, defining data schemas, managing data quality, and implementing robust ingestion workflows.
Create, alter, and validate Snowflake semantic views via the CLI. Automate the generation, documentation, and testing of semantic layer definitions to ensure model accuracy and star schema compliance.
Research technical documentation and automatically generate ready-to-use software agent skills in markdown format.
Generate production-ready Kubernetes manifests including Deployments, Services, CRDs, and more with built-in validation.
Generate optimized SQL queries from natural language. Supports BigQuery, PostgreSQL, MySQL, and Snowflake. Analyze database schemas, interpret business requirements, and output ready-to-run queries with explanations.
Aggressively prune grammatical scaffolding and filler text from inputs to optimize LLM token usage while retaining core semantic content.