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Found 4,647 Skills
Manage cloud infrastructure — monitor deployments, scale resources, manage databases, and handle domain operations across all supported providers.
8 finance skills. Trigger: financial modeling, market data, risk analysis, quantitative finance. Design: data sources, quantitative methods, and regulatory frameworks.
Internal sub-skill for job-hunt suite. Performs STAR alignment analysis per JD, then generates 3-piece tailored output (resume.md / opener.md / changelog.md). Enforces strict ethical boundaries — never fabricates experience or numbers. Do NOT invoke directly — use the job-hunt main skill instead.
Use version control as a craft — atomic commits, buildable history, useful PRs, bisect-friendly main, recoverable mistakes. Use this skill whenever the task involves writing commits or PRs, choosing a branching model, deciding rebase vs. merge, recovering from a force-push or accidentally-committed secret, debugging a regression with `git bisect`, structuring a long change as a series of small reviewable steps, or judging whether a repo's history is readable. Use it especially when reviewing commit messages, PR descriptions, branching strategies, or merge policies. Built on Tim Pope and Chris Beams on commit messages, Paul Hammant on trunk-based development, Vincent Driessen on GitFlow (and his 2020 note retiring it for SaaS), Linus Torvalds on never rebasing public commits, and the Google Engineering Practices CL guide.
Routes PubNub questions to the correct documentation source, MCP tool, and specialist skill. Classifies intent (chat vs non-chat, conceptual vs implementation, runtime testing vs analytics) and points the agent to the right next step. Use when a user mentions PubNub for the first time, asks "where do I start", "which docs", "what should I use", or any time the appropriate next skill is unclear.
Audit your biggest closed-won deals to find your PROVEN ideal customer profile, then find more accounts like them. Use whenever someone wants to analyze won deals, audit their best customers, see which companies generated the most revenue, find their real ICP, build a look-alike target list, segment customers by what actually pays, or learn which acquisition channel produced their best revenue. Triggers on: 'audit my biggest deals', 'which customers made us the most money', 'analyze my closed-won', 'what's my proven ICP', 'find more customers like my best ones', 'look-alike accounts', 'HubSpot deal analysis', 'revenue by account', 'which channel generated my best deals', 'acquisition source analysis'. For RevOps, Heads of Sales/Marketing, founders and growth leads doing ICP refinement, account-based targeting or pipeline/QBR review. Reads HubSpot via its MCP or a CSV export, then hands the profile to sales-nav-search-builder to generate the prospecting search. Maintained by La Growth Machine.
Use before any Luma / 拾光 / 拾光智能体 / 拾光工具 production workflow. Defines common luma-cli rules for auth, tool discovery, projects, artifacts, runtime resources, and safe agent behavior.
Validar prompts dirigidos a agentes de IA (Claude Code, Cursor, Copilot, etc.) contra reglas de redacción efectiva. Calcular un porcentaje de efectividad del prompt y devolver sugerencias de mejora concretas, más una propuesta de prompt reescrito. Cubre verbos no imperativos, lenguaje conversacional, acciones vagas, términos subjetivos, alcance difuso, prohibiciones implícitas, intenciones múltiples y nombres genéricos. Las reglas de detalle técnico (alcance, nombres exactos) se aplican solo a prompts de implementación; en prompts funcionales (user stories, descripciones de comportamiento) se marcan N/A. Usar siempre que el usuario pida validar, revisar, auditar, mejorar, corregir o "pulir" un prompt antes de enviarlo a un agente, o cuando pegue un prompt y pida feedback sobre cómo está redactado.
Use this skill to manage Google Cloud Workload Manager evaluations, rules, scanned resources, and validation results by using public client libraries and the REST API. Use when you need to inspect workload best-practice rules, create and run evaluations for Google Cloud general best practices, SAP, SQL Server, or custom organizational rules, review violations, export results to BigQuery, or automate Workload Manager through client libraries because no service-specific public CLI or MCP server is available. Don't use for general Google Compute Engine instance management, VPC configuration, or standard IAM auditing.
Builds, runs, debugs, and operates applications on AWS Lambda MicroVMs — Firecracker-isolated, snapshot-resumable serverless compute environments running inside a container with up to 8 hr lifetimes. Applicable when workloads need strong isolation between tenants, isolated serverless compute, sandbox compute, or secure multi-tenant execution. Also suited for AI/agent code-execution sandboxes, interactive code playgrounds and notebooks (Jupyter, REPLs, dev environments running user-supplied code), reinforcement-learning environments, multi-tenant CI executors and build runners, sessionful game or simulation servers, or isolated security scanners. Also applicable when the workload needs long-lived sessions, a real port-listening server (gRPC, WebSocket, custom TCP protocols), state preserved across periods of inactivity (suspend/resume), container-level access (FUSE, eBPF, custom syscalls), or session-affine routing.
Build read models and projections from event streams. Use when implementing CQRS read sides, building materialized views, or optimizing query performance in event-sourced systems.
Compress large language models using knowledge distillation from teacher to student models. Use when deploying smaller models with retained performance, transferring GPT-4 capabilities to open-source models, or reducing inference costs. Covers temperature scaling, soft targets, reverse KLD, logit distillation, and MiniLLM training strategies.