Built here
Building an AI agent
/ai--agent-builder
/ai--agent-builder is a Claude Code skill in the AI & Agents section. Designs and implements an LLM agent in your codebase: the loop, tools, memory, stop limits and a task-level eval suite to run before shipping.
Author's description
Build an AI agent - loop design, tool surface, memory, stop conditions, evals
Use it when
- You have a multi-step task that is hard to fully specify up front
- You want a model to call tools and keep iterating until it is done
- You need cost and iteration limits plus tests before shipping
Not for
- Fixed-sequence tasks, where code-orchestrated calls are enough
- Coordinating several agents at once (that is what ai--multi-agent is for)
What you get
Agent code in your repository (loop, tools, stop limits, logging) plus a suite of 10-20 test tasks, each with an automatic pass/fail check.
How to ask for it
/ai--agent-builder design an agent that handles support tickets/ai--agent-builder help me define stop conditions for my agent/ai--agent-builder what tools should I expose to this agent?
Install
curl -fsSL https://raw.githubusercontent.com/sgomez-dev/claude-skills/main/install.sh | bashAfter installing with the script, type /ai--agent-builder. Using Cursor, Windsurf or Codex? Platform guides
Questions about this skill
- Does it always build an agent?
- No. If the task is a fixed sequence of steps, it builds a code-orchestrated workflow instead. The agent loop is reserved for multi-step tasks that are hard to specify in advance and where errors are recoverable.
- What safety limits does it add?
- Maximum iterations, tokens or cost per run, and a wall-clock timeout, all configurable and logged when hit. Hard-to-reverse actions such as sends, deletes and payments are gated behind explicit confirmation.
- How does it check the agent works?
- With 10-20 representative tasks, each with a programmatic check on the outcome. The suite runs on every prompt or tool change and tracks success rate, iterations and cost per task.
Demo coming soon