codebase-onboarding
Helps your agent introduce a new code project to developers. It explains the structure, entry points, and suggests where to start exploring.
What it does
Helps you understand a new code project. It explains the overall structure, where to start looking, and who is responsible for each part.
When to use it
- ✓When you receive a new project and don't know where to start.
- ✓When you need to understand how different parts of the code connect.
- ✓When you want to know which file to look at first to understand a feature.
Example of what to ask your AI
“Explain to me how this code project works and which files I should look at first.”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
The AI uses a tool called Ontoly to analyze the code. It creates a project summary, identifies main entry points, and maps out different code sections.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add sickn33/agentic-awesome-skills --skill codebase-onboardingOr download just the file:
curl -L https://raw.githubusercontent.com/sickn33/agentic-awesome-skills/main/plugins/agentic-awesome-skills-claude/skills/codebase-onboarding/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
When to Use
- Use when this upstream workflow matches the user's stated goal.
- Use when the task requires the procedures documented in this skill.
Codebase Onboarding
Use this skill when the user asks for codebase onboarding using Ontoly evidence.
Required Workflow
Follow [the shared Ontoly workflow. Also read [graph evidence rules, [MCP usage, [best practices, and [fallback rules when the task requires detail.
Ontoly Capabilities
Use these capabilities first: ExplainArchitecture, FindEntrypoints, GraphStatistics, FindFeatureOwner, EvidencePack.
Output Contract
Return:
- answer or plan
- capabilities invoked
- graph evidence with node ids, edge types, source spans, and graph hash when available
- confidence: high, medium, or low
- fallback reason if repository files were inspected
Boundaries
Do not implement compiler, query, MCP, SDK, or business logic in the skill. Do not search repository files until Ontoly cannot answer or evidence must be confirmed.
Resources
- [Examples
- [Prompt template
- [Capability notes
Learn more
- Documentation: https://ontoly.xyz/docs
- This skill on the web: https://ontoly.xyz/skills#codebase-onboarding
- All Ontoly Agent Skills: https://ontoly.xyz/skills
- Install via skills.sh: https://www.skills.sh/?q=0xsarwagya/ontoly
Examples
User: Apply this skill to my current task.
Assistant: Follow the workflow in this skill, cite limitations, and ask before risky steps.
Limitations
- Imported upstream skill; verify credentials, permissions, and safety boundaries before execution.
- Does not replace environment-specific validation, testing, or maintainer review.
FAQ
What is Ontoly?
Ontoly is a tool that helps AI understand and summarize complex code projects.
What are 'entrypoints'?
These are the main starting points of a program or a specific feature.
Will the AI change my code?
No, the AI analyzes the code to give you information but doesn't make changes without your permission and only searches files if it can't get the answer otherwise.
Details
Original description by the author
Onboard a developer to a repository using Ontoly graph summaries. Use when asked to explain a new codebase, identify entrypoints, map packages, or suggest first files to inspect.
Popularity
- GitHub stars
- 48k
- Ranking position
- #2589
- License
- MIT
- Updated
- 10/15/2026
Comments
- …
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