What Are AI Agent Skills?
An agent skill is a reusable set of instructions, usually packaged as a SKILL.md file with any supporting resources. A compatible agent can use those instructions for a recurring task. The host determines how skills are discovered and what tools the agent can access; a markdown file does not grant permissions or enforce a tool allowlist by itself.
How Agent Skills Work
Each skill page shows its expected inputs and outputs, required tools, related build guides, and the SKILL.md file. Download the file and follow the installation method for your agent. Host support and skill discovery vary, so check the agent's current documentation before installing.
The instructions are readable markdown, which makes them straightforward to inspect and adapt. Portability is not automatic: tool names, directory conventions, permissions, and execution behavior depend on the host and any integrations you configure.
Review a skill before running it. Check commands, network destinations, credentials, and any external side effects, then configure permissions in the host. A SKILL.md file describes a workflow; it is not a security boundary.
Skills are deliberately small. A skill does one job -- researching leads, ingesting a document set, auditing a landing page -- and does it repeatably. That makes it easy to test, easy to hand to non-engineers, and easy to chain: a lead research skill can feed a cold email skill, which feeds a CRM automation skill. Treat them as building blocks for larger workflows rather than monolithic assistants.
What You Can Automate
The 10 downloadable skills below cover four types of workflows:
- Sales and outreach: Cold Email Sequence, and Sponsor Outreach cover lead research, message drafting, campaign setup, reply tracking, and handoff. Sending requires the listed messaging services and host permissions to be configured.
- Research and knowledge: Playwright Lead Research browses websites and extracts structured lead data, while RAG Document Ingestion chunks documents, generates embeddings, and builds a searchable knowledge base.
- Business operations: Neon CRM Automation scores and routes pipeline leads, the Internal Reporting Agent ships scheduled reports from your tools, and Landing Page Audit reviews pages for conversion, SEO, and UX issues.
- Engineering: MCP Server Creation scaffolds tool servers over the Model Context Protocol, Code Review Workflow automates pull-request review, and Multi-Agent Orchestrator coordinates specialized sub-agents.
Each skill page documents the required tools, example outputs, and the recipes that show how the underlying system is built.
Want these skills implemented for your business? explore our AI automation services.
Skills, Recipes, and Patterns: Which Do You Need?
Skills are instruction files you install into a compatible host and review before use. Recipes are step-by-step build-alongs that construct the system from scratch, so you understand and can customize every part. Patterns are design-level solutions to recurring agent problems like routing, chaining, and orchestration. If you want the outcome today, start with a skill; if you need to bend it to your environment, follow its related recipe.
Playwright Lead Research
Browse websites, search Google Maps, extract structured lead data, and compile research reports.
RAG Document Ingestion
Ingest documents, chunk them, generate embeddings, and build a searchable knowledge base.
Neon CRM Automation
Watch for new CRM leads, enrich with AI, auto-tag, score, and route them through a sales pipeline.
Sponsor Outreach
Research potential sponsors, draft personalized outreach, track responses, and manage a sponsorship pipeline.
Landing Page Audit
Analyze landing pages for conversion optimization, SEO, messaging, and UX, then produce an actionable audit report.
Cold Email Sequence
Research prospects, write personalized cold emails, schedule follow-ups, and track response rates.
Internal Reporting Agent
Gather data from multiple business tools, generate analysis reports, and distribute them via email or Slack on a schedule.
MCP Server Creation
Design and build MCP servers that expose custom tools, resources, and prompts for AI agents using the Model Context Protocol.
Code Review Workflow
Automate code review across PRs: analyze diffs, check for bugs, security issues, style violations, and generate structured review feedback.
Multi-Agent Orchestrator
Coordinate multiple specialist agents using the orchestrator-workers pattern: decompose tasks, delegate, monitor progress, and synthesize results.