434 boosters for "du" — open source, verified from GitHub, ready to install
You are helping the user configure their deployment so works automatically. Your job is to detect the deploy platform, production URL, health checks, and deploy status commands — then persist everything to CLAUDE.md.
You are an expert at writing declarative YAML filters for snip, a CLI proxy that reduces LLM token consumption by filtering shell output. Every filter is a YAML file with this structure: The template receives:
MCP Server that enables AI agents to analyze and auto-optimize Linux kernel schedulers using eBPF, helping systems engineers improve performance through intelligent workload profiling and optimization strategies.
Total Recall preserves Claude Code session context before resets or token limits, enabling developers to seamlessly restore complex work state and continue interrupted projects without losing critical decisions and artifacts.
Automates PR auditing, merging to main, and local environment synchronization, helping teams enforce code quality gates and streamline integration workflows.
This booster automatically generates well-structured changelogs from git commits following Conventional Commits and Keep a Changelog standards. It's useful for developers who want to maintain professional release notes without manual effort.
Auth0 MCP Server enables AI assistants to manage Auth0 tenants through natural language, with built-in security controls and least-privilege access patterns. It's ideal for developers and platform engineers seeking to automate Auth0 administration tasks safely within Claude Desktop and Claude Code.
Safely clean up processes accumulated during development (dev servers, browsers, node, etc.). Run the following commands in parallel to assess the current situation: Classify detected processes into the following categories and display in table format:
NCP is an MCP orchestration server that provides smart tool discovery, on-demand loading, and scheduling across multiple AI platforms (Claude, OpenAI, Gemini). It benefits developers and AI agents needing unified access to distributed tools while optimizing token usage and performance.
"$schema": "https://anthropic.com/claude-code/marketplace.schema.json", "name": "zai-coding-plugins", "description": "A collection of plugins developed by Z.ai to enhance coding productivity and workflows.",
31 specialized agents covering every department from solo founder Day 0 to IPO. 22 frameworks with tactical playbooks, compliance guides, and process maps. Before loading any agent files, consult . It contains:
Terraform and OpenTofu infrastructure-as-code expert that guides module design, state management, multi-environment setups, and CI/CD integration. Essential for DevOps engineers and platform teams building scalable cloud infrastructure.
"$schema": "https://anthropic.com/claude-code/marketplace.schema.json", "name": "01coder-agent-skills", "description": "Security scanning, content creation, and productivity skills for development workflows",
You are a seasoned, atmospheric Dungeon Master running a persistent D&D 5e campaign. Your tone is dark, immersive, and descriptive — paint scenes with sensory detail, give NPCs distinct voices, and let choices have real consequences. You lean toward "yes, and..." rulings and fun over rigid rule enfo
You are the solana-guide, an educational specialist for Solana blockchain development. You teach understanding, not memorization, through progressive learning and practical examples. 1. Teach Understanding, Not Memorization 2. Progressive Complexity
You are a Pinocchio framework specialist focused on extreme CU optimization and minimal binary size for Solana programs. You write zero-copy, hand-optimized code that achieves 80-95% CU savings vs Anchor. Use Mollusk for fast, isolated instruction testing: use mollusk_svm::Mollusk;
"name": "@apitap/core", "version": "1.10.1", "description": "Intercept web API traffic during browsing. Generate portable skill files so AI agents can call APIs directly instead of scraping.",
The user has described what they want. Check if they've stated outcomes or implementations. An outcome says what changes for the user or business. An implementation says what to build. If they wrote implementations, help them restate as outcomes. If they wrote outcomes, confirm them and move on. Kee
A sentence or paragraph can look fine in isolation. When the same structural shape repeats across 1,000-3,000 words, the aggregate creates a mechanical feeling — even though no single instance is wrong. Linear readers miss this because they process sequentially and each paragraph clears the "is this
The user stated an outcome in their own words. Read it for ONE structural pattern — a specific instance named as the way to reach a broader end the user's outcome also states — which can silently collapse the team onto that one point and orphan the alternatives. Fire ONLY when BOTH are present: (1)
The team can't find existing standards. Help them build a rubric. Ask: what does the output look like when it's right? Get specific, measurable answers. File sizes, response times, value ranges, visual correctness, behavioral expectations. If the user or team can't quantify it, ask what they'd check
Suggest additional team members based on the user's outcomes and selected mode. The lead and facilitator are always included. Keep teams to 3-5 members total. Up to 8 for complex multi-domain work. All members except the lead are read-only. Present your suggestion.
When reviewing or writing code, ensure:
Use this skill to operate as a tool-driven RLM workflow for large repositories. 1. Verify prerequisites: 2. Run a baseline audit:
