project-context-generation

Generates concise AGENTS.md instruction files by analyzing repository structure and conventions.

Updated Apr 20, 2026
One-click install
npx skills add https://github.com/astroville/sprout --skill project-context-generation-astroville
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: project-context-generation
Source: https://github.com/astroville/sprout/tree/main/.claude/skills/project-context-generation
Command: npx skills add https://github.com/astroville/sprout --skill project-context-generation-astroville

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Future agent sessions waste time rediscovering build commands, project structure, and conventions. This Skill analyzes a repository and produces a concise AGENTS.md that captures only the guidance future sessions repeatedly need. ## Core Features & Use Cases - Repository Analysis: Builds a mental model of the codebase, capturing build, test, lint, and verification commands plus module boundaries not obvious from names alone. - Context Curation: Records stack conventions, setup quirks, operational gotchas, and code intelligence output such as package structure and dependency graphs from hero scan. - In-Place Improvement: Updates an existing AGENTS.md rather than overwriting it, keeping the file actionable for agent execution instead of becoming a general README. - Use Case: After onboarding a new multi-language repository, run this Skill to produce an AGENTS.md so every future agent session starts with the correct commands and conventions. ## Quick Start Analyze this repository and generate a concise AGENTS.md with the build, test, and lint commands future agent sessions need.

Frequently Asked Questions about project-context-generation

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

FAQPage Schema
How do I create an AGENTS.md file for my repository?▼

Analyze the repository to identify build, test, and lint commands, module boundaries, and conventions, then write them as concise actionable guidance. Capture only instructions future sessions repeatedly need rather than restating the whole codebase.

What should an AGENTS.md file contain for AI coding agents?▼

Include build, test, lint, and verification commands, command ordering when it matters, non-obvious project structure, stack conventions, setup quirks, and references to existing rules files. Keep it concise and specific to the project.

Should I update an existing AGENTS.md or create a new one?▼

Improve the existing AGENTS.md in place when one is present. Preserve useful content, remove stale or generic advice, and add newly discovered commands or conventions rather than overwriting the file.

What are common mistakes when writing agent context files?▼

Common mistakes include restating the entire codebase, adding generic advice not specific to the project, and writing prose meant for humans instead of actionable instructions. Keep the file useful for future agent execution, not as a general README.

How does code intelligence output improve project context files?▼

Output from tools like `hero scan` provides package structure, key symbols, dependency graphs, and hot files. Including this orients future sessions quickly without requiring them to re-scan the repository.