186 boosters for "lm" — open source, verified from GitHub, ready to install
Connect a Kubernetes cluster (EKS, GKE, AKS, or KOPS) to CAST AI for cost optimization, autoscaling, and security scanning. Covers API key generation, Helm chart installation of the CAST AI agent, and Terraform provider setup. Log in to https://console.cast.ai and navigate to API > API Access Keys.
A skill for adapting and optimizing Hugging Face or custom LLM models to run efficiently on vLLM with Ascend NPU support, enabling developers to validate and deploy models with deterministic testing and single-commit delivery.
A Cursor-integrated coding standards and linting configuration toolkit for NeMo Curator projects, helping teams enforce consistent data processing code quality with Ruff-based rules and exceptions.
Claw Compactor is a 6-layer token compression skill for OpenClaw agents that reduces workspace token spend by 50–97% through deterministic rules and an LLM-driven memory system called Engram. It's designed for developers building token-efficient AI agents who need automatic cost optimization at session start.
"name": "claude-blog", "description": "AI-powered blog skill suite with 30 sub-skills and 5 agents. FLOW framework integration (Find/Optimize/Win, 30 evidence-led prompts), semantic topic-cluster planning + execution, multilingual publishing (translate/localize/locale-audit), Google API integration
Halmos is a symbolic execution tool for EVM smart contracts that integrates with Copilot to help developers write and verify property-based tests in Solidity. It enables security-focused developers to automatically find bugs and verify contract correctness using SMT solvers.
Automates the discovery, fixing, and PR management of GitHub issues by spawning sub-agents to implement solutions and handle code reviews. Developers working on active repositories benefit from reduced manual triage and implementation overhead.
A system prompt that guides LLMs to analyze Factorio game implementations and generate detailed natural language plans for achieving objectives. Useful for developers creating AI-driven game planning systems or educational tools.
Use this before submission when the empirical story is not yet locked. FSE reviewers are SE empiricists; the evaluation is where a good idea is won or lost. The organizing principle is on subjects and baselines a skeptic would accept.
LLM-first SEO analysis skill with 16 specialized sub-skills, 10 specialist agents, and 33 scripts for website, blog, and GitHub repository optimization. For prompt reliability in Codex/agent IDEs, map common user wording to a fixed workflow: When the user requests SEO analysis, follow this routing:
An orchestrator booster that automatically fetches GitHub issues, spawns AI sub-agents to implement fixes, opens pull requests, and manages review feedback. Ideal for teams looking to automate bug triage and fix workflows.
Always run before checking violations — it fixes indentation/spacing automatically: Save this script as and run for any module: """Fix checkstyle violations: SpringCatch, NeedBraces, SpringLambda, SpringTernary,
"name": "atlas-mcp-server", "version": "2.8.15", "description": "ATLAS (Adaptive Task & Logic Automation System): An MCP server enabling LLM agents to manage projects, tasks, and knowledge via a Neo4j-backed, three-tier architecture. Facilitates complex workflow automation and project management thr
"name": "mulmocast", "main": "lib/index.node.js", "types": "./lib/index.node.d.ts",
若用户没给时辰，必须主动询问，不要默认子时。时辰对四柱日柱和紫微命宫影响极大。 LLM 读 JSON 不如读结构化文本。把 Step 1 的 JSON 转成文墨天机风格的树状文本： 将 内容连同对应提示词一起送给 LLM 做分析。
Pulse Radar uses LLM pipeline to transform raw Telegram messages into structured knowledge. Core philosophy: Messages individually are noise; batched extraction reveals patterns. 1. JSON-only output — explicitly state "respond with ONLY JSON"
A clean, LLM-optimized MCP server that enables Claude to browse Reddit posts, search content, and analyze user data directly. Developers and AI builders benefit from seamless Reddit integration in their Claude-powered applications.
Query a structured, cross-referenced knowledge base of GPU kernel optimization for NVIDIA Blackwell (SM100) and Hopper (SM90). The repository update date is recorded in ; run for current corpus counts. Trigger this skill when the user asks about: Do NOT use this skill for:
A PHP SDK for building AI agents with structured outputs and multi-agent orchestration, enabling developers to decompose complex tasks into specialized subagents with isolated contexts and independent execution.
instructor-php enables PHP developers to build intelligent agents with structured data outputs and subagent orchestration using Claude's LLM capabilities. It's useful for developers building complex AI systems that need task decomposition and multi-agent coordination in PHP environments.
The Following is a next.js 15 project, react 19, typescript, shadcn ui, tailwind css project. It is an ai resume builder. It is called "ResumeLM". JSON Fields Structure:
You solve problems by decomposing them: break big tasks into smaller ones, delegate to sub‑agents, combine results. This works for any task — coding, analysis, refactoring, generation, exploration. Your original prompt is also available as a file at — use it when you need to manipulate the question
No database. No vectors. No manual saves. Just an LLM observer that compresses your conversations into prioritised notes, consolidates when they grow, and recovers anything missed. Five layers of redundancy, zero maintenance. ~$0.00/month (using free-tier models). While other memory skills ask you t
Graphsignal observes inference workloads from a sidecar process — the profiler. It never shares a process with CUDA: the profiler watches the workload externally via CUPTI, OTLP/gRPC, Prometheus scraping, and NVML. Auto-instrumentation covers vLLM, SGLang, and PyTorch out of the box. Two install pat
