do-agent-first-repo

Structure repositories and documentation so AI coding agents can work autonomously.

2|Updated May 25, 2026
One-click install
npx skills add https://github.com/edheltzel/Do-Skills --skill do-agent-first-repo-edheltzel
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: do-agent-first-repo
Source: https://github.com/edheltzel/Do-Skills/tree/main/skills/core/do-agent-first-repo
Command: npx skills add https://github.com/edheltzel/Do-Skills --skill do-agent-first-repo-edheltzel

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? AI coding agents fail when project knowledge lives in Slack threads, wikis, or people's heads instead of the repository. This Skill provides patterns for structuring a repo so agents can find context, follow architectural rules, and avoid replicating bad patterns. ## Core Features & Use Cases - Knowledge Hierarchy: Defines a layered documentation architecture with AGENTS.md, ARCHITECTURE.md, and a docs/ tree covering design docs, exec plans, product specs, and quality scores. - Progressive Disclosure: Organizes docs in three layers so agents start with minimal context and drill deeper via index files and cross-links. - Mechanical Enforcement: Shows how to encode architectural rules as custom linters with remediation messages, structural dependency tests, and layer boundary checks enforced in CI. - Entropy Management: Provides golden principles, automated violation scanning, quality scoring, and tech-debt tracking to prevent agent-generated code drift. - Use Case: When setting up a new project for agent-first development, use this Skill to create AGENTS.md and ARCHITECTURE.md, then add lint rules that fail CI when agents violate layer boundaries. ## Quick Start Ask the agent to restructure this repository for agent-first development, starting with an AGENTS.md entry point and an ARCHITECTURE.md codemap.

Frequently Asked Questions about do-agent-first-repo

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I make my repository agent-friendly for AI coding tools?▼

Start with an AGENTS.md entry point containing dev commands and repo structure, plus an ARCHITECTURE.md codemap with boundaries and invariants. Grow a docs/ tree with design docs, exec plans, and product specs as complexity demands, keeping all knowledge versioned in the repo.

What is progressive disclosure for AI agent context?▼

Progressive disclosure structures documentation in three layers: a ~100-line AGENTS.md entry point, an ARCHITECTURE.md for module relationships, and on-demand domain docs in docs/. Agents start with minimal context and drill deeper through index files and cross-links instead of loading everything upfront.

How do I enforce architecture rules for AI-generated code?▼

Encode rules as custom linters with remediation messages, structural dependency tests, and layer boundary checks that fail CI. Prose documentation gets ignored by agents, while CI failures block merges and the lint error messages themselves tell the agent how to fix violations.

Why does AI-generated code accumulate technical debt faster?▼

Agents replicate existing patterns including bad ones, so a suboptimal pattern used 15 times becomes the dominant convention. Counter this with golden principles, automated violation scans, small continuous refactoring PRs, and quality scores tracked per domain in the repo.

When should I not use the agent-first repo approach?▼

Small projects do not need the full docs/ tree; start with just AGENTS.md and ARCHITECTURE.md and grow as complexity demands. Subjective rules like preferring composition over inheritance cannot be mechanically enforced and are better left as documentation.