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.
npx agentmods add skills/macromania/agentop/code-qualitynpx skills add macromania/agentop --skill code-qualitygit clone --depth 1 https://github.com/macromania/agentopWhat 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 | $0.00068 | $0.02466 |
| Opus 5 | $0.00034 | $0.01233 |
| Sonnet 5 | $0.00014 | $0.00493 |
| Haiku 4.5 | $0.00007 | $0.00247 |
Grade A, and why
code-quality 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 2d 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 — 392 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Quality & Refactoring
Best practices for writing clean, maintainable, and high-quality code based on proven patterns from Vercel, Anthropic, and industry standards.
When to Use This Skill
- Reviewing code for quality issues
- Refactoring existing code
- Reducing complexity
- Improving testability
- Applying design patterns
- Code review feedback
Code Quality Principles
SOLID Principles
// ❌ BAD: Class doing too much (violates SRP)
class TaskManager {
createTask(title: string) { /* ... */ }
updateTask(id: string, data: Partial<Task>) { /* ... */ }
deleteTask(id: string) { /* ... */ }
sendTaskNotification(taskId: string) { /* ... */ }
generateTaskReport(taskId: string) { /* ... */ }
syncTaskToExternalService(taskId: string) { /* ... */ }
}
// ✅ GOOD: Single Responsibility Principle
class TaskRepository {
create(title: string): Task { /* ... */ }
update(id: string, data: Partial<Task>): Task { /* ... */ }
delete(id: string): void { /* ... */ }
}
class TaskNotificationService {
notify(taskId: string): void { /* ... */ }
}
class TaskReportGenerator {
generate(taskId: string): Report { /* ... */ }
}
Open/Closed Principle
// ❌ BAD: Must modify class to add new behavior
class AttentionHandler {
handle(type: AttentionType, step: AgentStep) {
if (type === 'supervised') {
// supervised logic
} else if (type === 'delegated') {
// delegated logic
} else if (type === 'sensitive') {
// sensitive logic
}
// Adding new type requires modifying this class
}
}
// ✅ GOOD: Open for extension, closed for modification
interface AttentionStrategy {
handle(step: AgentStep): Promise<boolean>;
}
class SupervisedStrategy implements AttentionStrategy {
async handle(step: AgentStep): Promise<boolean> {
// Always require approval
return await requestUserApproval(step);
}
}
class DelegatedStrategy implements AttentionStrategy {
async handle(step: AgentStep): Promise<boolean> {
// Auto-approve
return true;
}
}
class SensitiveStrategy implements AttentionStrategy {
private sensitiveTools = ['run_command', 'delete_file'];
async handle(step: AgentStep): Promise<boolean> {
if (this.sensitiveTools.includes(step.toolCall?.name ?? '')) {
return await requestUserApproval(step);
}
return true;
}
}
// New attention types just add new strategy classes
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.
- 2d ago First seen · 392 lines · 68 tokens per session scan A 781f40277c42
code-quality is a skill published in the GitHub repository macromania/agentop (10 stars, last pushed 5mo ago), licensed MIT. It adds 68 tokens to every session and 2,466 once invoked, about $0.0003 per session on Opus 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 2026-08-31.
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