Hand-crafted skills for building AI agents — each one distilled from a technique used and proven in real Agentailor projects, not auto-generated.
These are skills for agent builders: drop them into a skill-aware coding agent (Claude Code, or any tool that reads the AgentSkills spec) so it can help you design agents to a consistent, production-tested standard. They pair with the deep-dive write-ups on the Agentailor blog.
| Skill | What it does |
|---|---|
agent-prompt-engineering |
Design system prompts for autonomous, tool-using agents. Covers the principles, heuristics, thinking guidance, and evaluation strategy that make agents reliable in a loop — with worked prompt examples and the anti-patterns to avoid. Source: The Art of Agent Prompting. |
tool-design |
Design tools an AI agent can actually use — framework- and language-agnostic (MCP, LangChain/LangGraph, function-calling; TypeScript, Python, …). Five production-tested principles, a validation checklist, and worked examples across surfaces and languages. Source: Writing Effective Tools for AI Agents. |
More skills will be added here as they're proven useful in practice.
Each skill is a directory with a SKILL.md following the AgentSkills spec:
---
name: skill-name # lowercase, hyphens only, max 64 chars; matches the directory name
description: What this skill does and when to use it. # max 1024 chars — this is the trigger
---The Markdown body holds the instructions. Skills follow the standard progressive-disclosure convention: keep SKILL.md lean and move detailed material into a references/ directory (optionally scripts/ and assets/), loaded only when needed.
skills/
└── <skill-name>/
├── SKILL.md # required: frontmatter + instructions
├── references/ # optional: deep-dive docs loaded on demand
├── scripts/ # optional: executable helpers
└── assets/ # optional: templates and resources
We deliberately keep skills:
- Framework-independent where the idea allows — a good tool-design principle holds whether you use MCP, LangChain, or raw function calling. (Some skills are legitimately framework-specific; that's fine when the pattern itself is.)
- Language-neutral where the idea allows — the same design thinking maps onto TypeScript, Python, and beyond.
- Behavior-first — they describe what an agent should do, not how one library does it.
In a coding agent: point a skill-aware agent (e.g. Claude Code) at this repo, or copy a skill directory into your agent's skills folder, and let it load the skill when the task matches the description.
As a reference: read the SKILL.md and its references/ directly — they stand on their own as guides.
- AgentSkills Specification
- Agentailor blog — the articles behind these skills
- Agentailor — the hub for developers building AI agents