sublinkPro is a web application for managing proxy subscriptions, including importing providers, testing speed, routing traffic through relays, monitoring usage, and managing services through Telegram. It is built with Go on the backend and React on the frontend for people who manage proxy configurations and network traffic.
Borrowing it
Nothing to install: this file belongs to ZeroDeng01/sublinkPro. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/ZeroDeng01/sublinkPro/main/.agents/skills/performance-check/SKILL.mdgit clone --depth 1 https://github.com/ZeroDeng01/sublinkProWrote 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/skills/zerodeng01/sublinkpro/performance-check)<a href="https://agentmods.dev/skills/zerodeng01/sublinkpro/performance-check"><img src="https://agentmods.dev/badge/skills/zerodeng01/sublinkpro/performance-check/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/skills/zerodeng01/sublinkpro/performance-check"><img src="https://agentmods.dev/badge/skills/zerodeng01/sublinkpro/performance-check.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00036 | $0.01727 |
| Opus 5.5 | $0.00014 | $0.00691 |
| Sonnet 5.5 | $0.00007 | $0.00345 |
| Haiku 4.5 | $0.00004 | $0.00173 |
Grade A, and why
performance-check 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 2mo 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 — 225 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance Check Skill
This skill provides a comprehensive performance review checklist for code changes that may impact application performance, scalability, or resource usage.
When to use: When making changes to:
- Database queries and models
- API endpoints (especially list/search operations)
- Frontend rendering logic
- Background jobs and scheduled tasks
- Caching mechanisms
- Large data processing
- File operations
- Network requests
- Recursive algorithms
Performance Check Checklist
🗄️ 1. Database Query Optimization
Check for:
- N+1 query problem: Are related records loaded efficiently?
- Missing indexes: Are frequently queried columns indexed?
- **Select ***: Are only needed columns selected?
- Unnecessary joins: Are all joins necessary?
- Query in loop: Are queries executed inside loops?
- Pagination: Are large result sets paginated?
- Eager loading: Are associations preloaded when needed?
Detailed guide: references/database-optimization.md (includes code examples)
⚡ 2. API Response Optimization
Check for:
- Response size: Are responses minimized (exclude unnecessary fields)?
- Pagination: Are large lists paginated?
- Filtering: Are list endpoints filterable to reduce data?
- Compression: Is gzip compression enabled?
- Caching headers: Are appropriate cache headers set?
- Partial responses: Can clients request only needed fields?
Detailed guide: references/api-optimization.md (includes load testing example)
🎨 3. Frontend Rendering Optimization
Check for:
- Unnecessary re-renders: Are components optimized with
React.memo/useMemo/useCallback? - Large lists: Are large lists virtualized (>100 items)?
- Heavy computations: Are expensive calculations memoized?
- Bundle size: Are large dependencies code-split?
- Image optimization: Are images lazy-loaded and properly sized?
- Debouncing/Throttling: Are frequent events (scroll, input) debounced?
What ships with it
8 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/algorithm-complexity.md 4.1 KB
- references/api-optimization.md 3.0 KB
- references/caching-strategies.md 3.7 KB
- references/concurrency-guide.md 5.4 KB
- references/database-optimization.md 4.1 KB
- references/frontend-optimization.md 3.9 KB
- references/memory-management.md 4.7 KB
- references/network-optimization.md 3.9 KB
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.
- 2mo ago First seen · 225 lines · 36 tokens per session scan A d0ad520782f9
performance-check is a skill published in the GitHub repository ZeroDeng01/sublinkPro (1,727 stars, last pushed yesterday), licensed MIT. It adds 36 tokens to every session and 1,727 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.
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