productivity▌

Validate and standardize SKILL.md files against the Agent Skills specification. \n \n Validates frontmatter fields (name, description, allowed-tools, metadata) and enforces naming conventions, length constraints, and format rules \n Converts legacy skill formats to standard structure, including section heading normalization and directory layout alignment \n Provides templates and step-by-step guidance for creating new skills, improving descriptions for reliable triggering, and batch-validating s

Fast JavaScript/TypeScript development with Bun runtime, including package management, testing, bundling, and Node.js migration. \n \n Native TypeScript and JSX support with no transpiler required; 10-100x faster package installation and ~25ms startup time compared to Node.js \n Built-in tools: HTTP/WebSocket server, SQLite database, test runner, bundler, and password hashing via Bun.serve() , Bun.sql() , bun test , and Bun.build() \n File system and environment variable APIs ( Bun.file() , auto

Identifies high-quality leads by analyzing your business, searching for target companies, and ranking them with personalized outreach strategies. \n \n Analyzes your product/service and ideal customer profile to find matching companies based on industry, size, technology stack, and pain points \n Prioritizes leads with fit scores (1-10) and provides decision-maker titles, LinkedIn URLs, and company context for each prospect \n Generates personalized outreach strategies, value propositions, and c

Web search with LLM-optimized results, relevance scoring, and flexible filtering. \n \n Supports four search depth modes (ultra-fast, fast, basic, advanced) with configurable latency and relevance tradeoffs \n Includes domain filtering, time range constraints, date ranges, country boosting, and raw content extraction \n Returns results with title, URL, content snippet, and relevance score; optional image results and favicons \n Automatic OAuth authentication via Tavily MCP server or API key conf

Reference guide for building agents and workflows with current Mastra APIs. \n \n Always verify against embedded docs in node_modules/@mastra/*/dist/docs/ (installed version) or remote docs at https://mastra.ai/llms.txt before writing code; training data is outdated \n Core building blocks: Agents (autonomous, decision-making), Workflows (structured sequences), Tools (extend capabilities), Memory (maintain context), and RAG (external knowledge) \n Requires ES2022 modules in TypeScript config and

Pre-install security vetting for OpenClaw skills using a structured red-flag checklist. \n \n Evaluates metadata, permission scope, and content against critical, warning, and informational risk categories \n Detects typosquatting, credential file references, obfuscated content, and command injection patterns \n Flags high-risk permission combinations like network + shell that enable data exfiltration \n Produces a standardized vetting report with verdict (Safe/Warning/Danger/Block) and install r

ln-302-task-replanner

Build 3-5 year financial models with revenue projections, cost structures, and scenario planning for startups. \n \n Cohort-based revenue modeling with customer acquisition, retention, and ARPU inputs; supports SaaS, marketplace, e-commerce, and services business models \n Comprehensive cost structure breakdown across COGS, S&M, R&D, and G&A with fixed vs. variable categorization and scaling assumptions \n Cash flow analysis including monthly burn rate, runway calculation, and fun

In-app paywall and upgrade screen optimization for converting free users to paid tiers. \n \n Covers feature gates, usage limits, trial expiration, and time-based prompts with specific component templates and copy patterns for each trigger type \n Emphasizes value demonstration before the ask, with guidance on timing, frequency rules, and friction-free upgrade flows \n Includes A/B testing framework covering headline variations, pricing presentation, trigger timing, and key metrics like conversi

Comprehensive guide to implementing structured, secure, and performant logging across applications. Covers log levels, structured logging formats, contextual information, PII protection, and centralized logging systems.