# Iterated Agent Loop Builder

Builds a repo-local skill and a GitHub Actions workflow for an iterated coding agent.

- Repository: https://github.com/humanlayer/skills (5529 stars)
- Category: DevOps
- License: MIT
- Last updated: 2026-11-01
- Runs scripts: yes, review before use

## Install

Claude Code: `npx skills add humanlayer/skills --skill build-iterated-agentic-loop -g -a claude-code -y`
Codex: `npx skills add humanlayer/skills --skill build-iterated-agentic-loop -g -a codex -y`
Cursor: `npx skills add humanlayer/skills --skill build-iterated-agentic-loop -g -a cursor -y`
Gemini CLI: `npx skills add humanlayer/skills --skill build-iterated-agentic-loop -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add humanlayer/skills`

## Description

build a repo-local skill and install a matching iterated coding-agent GitHub Actions workflow, prompt, memory file, and reference templates

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Build Iterated Agentic Loop

Use this skill when the user wants to turn a repeatable agent task into a repo-local skill plus a GitHub Actions workflow that runs a coding agent on a schedule, manually, or both.

The target shape is an iterated agentic loop: a focused skill defines the agent's judgement, a workflow invokes a coding agent with a repo-specific prompt, an agent-memory file carries standing feedback between runs, and each workflow labels its PRs so only one open PR exists per loop. The `narrow-react-prop-types` skill is the concrete reference pattern.

## Outputs

Create or update these files in the target repo:

- `.claude/skills/<skill-name>/SKILL.md` for the repo-local agent behavior.
- `.github/workflows/agent-<task-name>.yml` for the recurring coding-agent automation.
- `.github/agent-memory/<task-name>.md` for stable feedback and scope constraints.
- Optional references under `.claude/skills/<skill-name>/references/` when the skill needs templates, examples, or long supporting material.

## Workflow

### 1. Explore the target repo

Read before asking setup questions:

- Existing `.github/workflows/*.yml` and `.github/actions/**` to understand runner, checkout, dependency install, cache, and PR patterns.
- Package manager files such as `package.json`, `bun.lock`, `pnpm-lock.yaml`, `yarn.lock`, `package-lock.json`, `pyproject.toml`, `go.mod`, or `Cargo.toml`, or other package management-related files
- Existing validation scripts, especially typecheck, lint, test, quality, format, and package-scoped commands.
- Existing `.claude/skills` and `.agents/skills` to avoid duplicating conventions.

Completion criterion: you can name the repo's package manager, install command, likely validation commands, and existing workflow conventions.

### 2. Ask setup questions

Walk the user through these decisions. Recommend defaults from repo evidence instead of presenting a blank form.

The rest: https://github.com/humanlayer/skills/blob/HEAD/plugins/build-iterated-agentic-loop/skills/build-iterated-agentic-loop/SKILL.md