57 boosters for "engineering" — open source, verified from GitHub, ready to install
Get Shit Done (GSD) is a meta-prompting and context engineering system that helps developers coordinate AI-assisted workflows across multiple platforms while preventing quality degradation from context window bloat. Developers building with Claude, OpenCode, Gemini, and Codex benefit from its structured Plan→Execute→Verify→Complete pipeline.
A specialized agent that transforms complex technical concepts into clear, developer-friendly documentation for APIs, READMEs, and tutorials. Ideal for engineering teams, open-source maintainers, and anyone who needs to document code quickly and effectively.
Incident Response Commander is an expert agent that guides engineering teams through production incident management, post-mortems, and on-call process design. It's designed for SREs, incident commanders, and reliable engineering organizations seeking structured incident coordination.
A developer advocate agent that helps teams build engaged developer communities, create technical content, and optimize developer experience through authentic engineering engagement. Best suited for product managers, DevRel teams, and engineering leads looking to improve platform adoption and developer satisfaction.
A senior pre-sales engineering agent that handles technical discovery, demo engineering, and POC scoping to win technical decisions and close deals. Ideal for B2B SaaS teams, sales leaders, and product managers who need to bridge technical capabilities with business outcomes.
An expert SRE agent that helps teams define SLOs, manage error budgets, build observability systems, and reduce toil in production environments. Ideal for engineering leaders and platform teams scaling reliable systems.
A hands-on short-video editing coach that guides users through the complete post-production pipeline across CapCut Pro, Premiere Pro, DaVinci Resolve, and Final Cut Pro. Ideal for content creators, video editors, and filmmakers seeking professional-grade editing expertise and workflow optimization.
The most comprehensive open-source library of Claude Code skills and agent plugins — also works with OpenAI Codex, Gemini CLI, Cursor, and 7 more coding agents. Reusable expertise packages covering engineering, DevOps, marketing, compliance, C-level advisory, and more. ![License: MIT](https://openso
A system prompt for Claude Code that enforces defensive security practices and provides CLI guidance, designed to help developers safely use Claude for software engineering tasks while preventing misuse.
"name": "pro-workflow", "description": "Complete AI coding workflow system. Context engineering, agent teams, 18 hook events, 6 agents, 14 skills, 9 guides, cross-agent support, and searchable learnings.", "name": "Rohit Ghumare",
"name": "taches-cc-resources", "description": "Curated Claude Code skills and commands for prompt engineering, MCP servers, subagents, hooks, and productivity workflows", "name": "Lex Christopherson",
A structured debugging methodology that guides developers through systematic root-cause analysis before implementing fixes, compatible with Claude Code and Cursor. Developers benefit by reducing debugging time and avoiding hasty code changes.
Use this agent to review existing code, audit plans, evaluate product requirements, or get architectural guidance that balances pragmatism, user experience, and security. This includes code reviews, plan audits, architecture reviews, security assessments, or when building engineering and development plans from requirements. Use proactively after significant code changes or before merging.
Use this agent when documentation in the `architecture/` directory needs to be updated or created for a specific file after implementing a feature, fix, refactor, or behavior change. Launch one instance of this agent per file that needs updating. This agent maintains the *contents* of architecture documentation files — it does not decide which files exist or how the directory is organized.\n\nExamples:\n\n- Example 1:\n Context: A developer just finished implementing OPA policy evaluation in the sandbox system.\n user: "I just finished implementing the OPA engine in crates/openshell-sandbox/src/opa.rs. Update architecture/sandbox.md to reflect the new policy evaluation flow."\n assistant: "I'll launch the arch-doc-writer agent to update the sandbox architecture documentation with the new OPA policy evaluation details."\n <uses Task tool to launch arch-doc-writer with instructions to update architecture/sandbox.md>\n\n- Example 2:\n Context: A refactor changed how the HTTP CONNECT proxy handles allowlists.\n user: "The proxy allowlist logic was refactored. Please update architecture/proxy.md."\n assistant: "Let me use the arch-doc-writer agent to synchronize the proxy documentation with the refactored allowlist logic."\n <uses Task tool to launch arch-doc-writer with instructions to update architecture/proxy.md>\n\n- Example 3:\n Context: After implementing a new CLI command, the assistant proactively updates docs.\n user: "Add a --rego-policy flag to the CLI."\n assistant: "Here is the implementation of the --rego-policy flag."\n <implementation complete>\n assistant: "Now let me launch the arch-doc-writer agent to update the CLI architecture documentation with the new flag."\n <uses Task tool to launch arch-doc-writer with instructions to update architecture/cli.md>\n\n- Example 4:\n Context: A user wants high-level overview documentation for a non-engineering audience.\n user: "Update architecture/overview.md with a non-engineer-friendly explanation of the sandbox system."\n assistant: "I'll launch the arch-doc-writer agent to create an accessible overview of the sandbox system for non-technical readers."\n <uses Task tool to launch arch-doc-writer with audience=non-engineer directive>\n\n- Example 5:\n Context: Multiple files need updating after a large feature lands.\n user: "I just landed the network namespace isolation feature. Update architecture/sandbox.md and architecture/networking.md."\n assistant: "I'll launch two arch-doc-writer agents — one for each file — to update the documentation in parallel."\n <uses Task tool to launch arch-doc-writer for architecture/sandbox.md>\n <uses Task tool to launch arch-doc-writer for architecture/networking.md>
pycse is a Python library that assists with scientific computing tasks including nonlinear regression, uncertainty quantification, design of experiments, and neural network-based modeling. It's useful for researchers, engineers, and data scientists working on numerical optimization, experimental design, and uncertainty analysis.
"name": "compound-knowledge-plugin", "url": "https://every.to" "description": "Workflows for knowledge work that compounds over time",
"name": "claude-prompts", "description": "Hot-reloadable versioned prompts with easy tools for prompt engineering, chain workflows, quality gates. Symbolic syntax: >>prompt --> >>chain @framework :: 'gate'", "homepage": "https://github.com/minipuft/claude-prompts",
You are an expert in prompt engineering and systematic application of prompting frameworks. Help users transform vague or incomplete prompts into well-structured, effective prompts through analysis, dialogue, and framework application. When a user provides a prompt to improve, analyze across dimensi
"description": "Harness Engineering plugin exposing executable fitness functions for architecture quality, change-aware validation, and MCP-powered review context.", "version": "0.1.14", "homepage": "https://github.com/phodal/entrix",
spec-gen automates the reverse-engineering of codebases into structured OpenSpec specifications through LLM-powered static analysis, enabling developers to maintain accurate, living documentation that reflects actual code behavior rather than intent.
"name": "harness-mcp-v2", "description": "Give AI agents full access to the Harness.io platform — manage pipelines, deployments, cloud costs, chaos engineering, feature flags, SEI, and 125+ resource types through 11 MCP tools", "main": "build/index.js",
You are a creative director specializing in AI image generation prompt engineering. Your job is to take a user's rough idea, image reference, or existing prompt and transform it into an optimized master prompt that produces exceptional results from image generation models. You have access to a compr
A progressive-disclosure skill for ROS 2 development — from first workspace to production fleet deployment. Each section below gives you the essential decision framework; detailed patterns, code templates, and anti-patterns live in the
"name": "brooks-lint", "description": "AI code reviews grounded in six classic engineering books — decay risk diagnostics with book citations, severity labels, and four analysis modes (PR review, architecture audit, tech debt, test quality)", "name": "hyhmrright",
