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/smart-explore)<a href="https://agentmods.dev/rules/gktuoktay/ai-skills/smart-explore"><img src="https://agentmods.dev/badge/rules/gktuoktay/ai-skills/smart-explore/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/smart-explore"><img src="https://agentmods.dev/badge/rules/gktuoktay/ai-skills/smart-explore.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 | $0.01060 |
| Opus 5 | $0.00000 | $0.00530 |
| Sonnet 5 | $0.00000 | $0.00212 |
| Haiku 4.5 | $0.00000 | $0.00106 |
Grade A, and why
smart-explore 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 — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Intelligent Codebase Exploration and Navigation
Navigating a large, unfamiliar codebase can be overwhelming. Relying solely on manual file browsing is inefficient. This guide covers strategies for rapidly understanding code architecture and finding specific logic.
1. Grep/Ripgrep Patterns for Finding Code
Ripgrep (rg) is the fastest tool for text-based searching.
- Find Function Definitions: To find where a function is defined, search for keywords like
def,class, orfunction.rg "function processOrder"orrg "const processOrder ="
- Find Class Definitions:
rg "class PaymentGateway"
- Filter by File Type:
rg "TODO" -t py(Only search Python files)
- Exclude Directories:
rg "password" --glob "!tests/*" --glob "!node_modules/*"
- Case Insensitive:
rg -i "user_id"
2. AST-Based Exploration
While rg is fast, it lacks context. AST (Abstract Syntax Tree) tools understand code structure.
- LSP (Language Server Protocol): Use IDE features (Go to Definition, Find All References). These are vastly superior to text search.
- Tree-sitter: Used in modern editors (Neovim, Zed) for precise syntax highlighting and structural navigation.
- AST Grep (
sg): Allows searching code by structure rather than exact text matches (e.g., finding all try/catch blocks that silently ignore errors).
3. Finding Entry Points and Hot Paths
When starting in a new repository, find where execution begins.
- Web Apps: Look for
index.js,main.ts,App.tsx,wsgi.py, ormain.go. - Routing: Search for router definitions (e.g.,
rg "react-router",rg "@app.route",rg "router.get"). This maps URLs to specific controllers. - Package Manifests: Check
package.json,Cargo.toml, orMakefilefor start commands (e.g.,npm run start). The script defined there points to the entry point.
4. Tracing Function Call Chains
To understand a feature, trace its execution path.
- Identify the Trigger: Find the UI button click, API endpoint, or cron job schedule.
- Follow the Data: Look at the arguments passed to the controller.
- Drill Down: Use "Go to Definition" to jump through the service layer, repositories, and finally to the database queries.
- Take Notes: Maintain a scratchpad documenting the call stack (e.g.,
Route -> UserController -> AuthService -> DB).
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 · 73 lines · 1,060 tokens per session scan A 5100d6dfeec4
smart-explore 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 1,060 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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