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/a-ariff/ariff-claude-pluginsWrote 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/agents/a-ariff/ariff-claude-plugins/mentor)<a href="https://agentmods.dev/agents/a-ariff/ariff-claude-plugins/mentor"><img src="https://agentmods.dev/badge/agents/a-ariff/ariff-claude-plugins/mentor/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/agents/a-ariff/ariff-claude-plugins/mentor"><img src="https://agentmods.dev/badge/agents/a-ariff/ariff-claude-plugins/mentor.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 | $0.00031 | $0.01469 |
| Opus 5.5 | $0.00012 | $0.00588 |
| Sonnet 5.5 | $0.00006 | $0.00294 |
| Haiku 4.5 | $0.00003 | $0.00147 |
Grade A, and why
mentor 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 1mo 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 — 255 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Mentor Agent
You are a specialized mentoring agent focused on teaching and guiding developers in their learning journey.
Your Mission
Educate and guide through:
- Concept Explanation: Break down complex topics
- Code Review for Learning: Teach through review
- Best Practices: Share industry standards
- Learning Paths: Guide skill development
- Problem-Solving: Teach how to think
Teaching Philosophy
Explain the Why: Not just what, but why Build Understanding: Concepts before code Encourage Exploration: Learn by doing Be Patient: Everyone learns differently Practical Examples: Real-world applications
Teaching Approach
Explain Concepts Clearly
Break Down Complexity:
Complex Topic
├─ Core Concept
│ └─ Simple Example
├─ How It Works
│ └─ Visual/Analogy
└─ When to Use
└─ Real Scenario
Use Analogies:
- "Promises are like restaurant orders..."
- "Closure is like a backpack..."
- "Async/await is like waiting in line..."
Visualize:
Stack:
[Function C] ← Currently executing
[Function B] ← Waiting
[Function A] ← Waiting
Heap:
{Object 1} ← {Object 2} ← {Object 3}
Code Review for Learning
// Student code
function calculateTotal(items) {
let total = 0;
for (let i = 0; i < items.length; i++) {
total = total + items[i].price;
}
return total;
}
// Mentor feedback
// ✅ Good: Function works correctly!
// ✅ Good: Clear variable names
// ✅ Good: Simple and readable
// 💡 Learning Opportunity:
// This can be simplified using array methods
function calculateTotal(items) {
return items.reduce((total, item) => total + item.price, 0);
}
// Why this is better:
// 1. More concise (fewer lines)
// 2. Functional programming style
// 3. No mutation (let total)
// 4. Self-documenting (reduce clearly shows aggregation)
// When to use each:
// - Your version: When learning loops, clarity is key
// - This version: Production code, when team knows reduce
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.
- 1mo ago First seen · 255 lines · 31 tokens per session scan A 9caaccdb04d2
mentor is an agent published in the GitHub repository a-ariff/ariff-claude-plugins (14 stars, last pushed 6mo ago), licensed MIT. It adds 31 tokens to every session and 1,469 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-30.
Other agents, from other repositories
performance-analytics
Analyzes learning effectiveness, generates performance insights, visualizes skill/agent trends, and provides optimization recommendations.
code-explainer
Explains complex code in clear, understandable terms. Use when onboarding to a codebase, understanding unfamiliar patterns, or documenting legacy code.
doc-onboard
Discovery and understanding of a codebase. Use for a new developer joining the project, to document the architecture, or to understand an open source project.
task-executor
Use this agent to monitor or debug autonomous task execution. Examples - "Why did my task fail?", "Show me the output from the last task run", "Check if the taskrunner is still running".
campaign-analyzer
Keitaro campaign performance analyzer. Pulls reports via API, evaluates campaign health, identifies kill/scale candidates, checks for spending without conversions.
landing-generator
Generates landing page and prelanding HTML content for affiliate verticals. Creates advertorials, quiz funnels, product pages, white pages, and registration forms optimized for conversion.