Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/GktuOktay/ai-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/rules/gktuoktay/ai-skills/learn-codebase)<a href="https://agentmods.dev/rules/gktuoktay/ai-skills/learn-codebase"><img src="https://agentmods.dev/badge/rules/gktuoktay/ai-skills/learn-codebase/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/rules/gktuoktay/ai-skills/learn-codebase"><img src="https://agentmods.dev/badge/rules/gktuoktay/ai-skills/learn-codebase.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.01122 |
| Opus 5 | $0.00000 | $0.00561 |
| Sonnet 5 | $0.00000 | $0.00224 |
| Haiku 4.5 | $0.00000 | $0.00112 |
Grade A, and why
learn-codebase scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Learn Unfamiliar Codebase Skill
Overview
This skill provides a systematic approach to rapidly onboarding onto, understanding, and navigating large, unfamiliar codebases. It is designed to move an agent from zero knowledge to productive contribution in the shortest time possible by prioritizing high-signal files and architectural patterns.
Phase 1: The First-Pass Strategy (High-Level Context)
Do not dive into source code immediately. Understand the box before looking inside.
1. Documentation & Manifests
Read these files first to understand what the project is, what it depends on, and how it is built.
README.md,CONTRIBUTING.md,ARCHITECTURE.md- Package manifests:
package.json(Node),pom.xml(Java),Cargo.toml(Rust),go.mod(Go),Podfile/Package.swift(iOS),requirements.txt/pyproject.toml(Python).
Goal: Answer "What are the core dependencies?" (e.g., React, Express, CoreData, Django).
2. Directory Structure Analysis
Use directory listing tools to get a bird's-eye view. Look for standard conventions.
src/,lib/,app/-> Source code.tests/,spec/,__tests__/-> Testing structure.config/,scripts/,docker/-> Infrastructure.
Goal: Answer "How is the code organized?" (e.g., by feature, by layer/type, monolith vs. microservices).
Phase 2: Finding Entry Points
To trace execution, you must know where it begins.
- Web Apps: Look for
index.js,main.ts,App.tsx,pages/_app.tsx(Next.js). - Backend APIs: Look for
server.js,main.go,manage.py,Program.cs, routes configurations. - Mobile Apps: Look for
AppDelegate.swift,@main struct App,MainActivity.java. - CLIs: Look for
bin/,cli.js,main.rs.
Phase 3: Identifying Architectural Patterns
Analyze the code organization to determine the architectural style. Look for:
- MVC (Model-View-Controller): Are there directories explicitly named
models,views,controllers? - Clean Architecture / Hexagonal: Are there layers for
domain,usecases,infrastructure,adapters? - Feature-Based Modular: Is code grouped by domain concept? (e.g.,
src/features/authentication/,src/features/users/). - State Management: Look for Redux (
store/,reducers/), Vuex, Context APIs, or core database abstraction layers (ORMs, DAOs).
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 86 lines · 1,122 tokens per session scan A ed988cc0ba2f
learn-codebase is a cursor rule published in the GitHub repository GktuOktay/ai-skills (2 stars, last pushed 8d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,122 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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