latency-tracker
Per-call and aggregated latency tracking for MEV infrastructure. Use when implementing performance monitoring or debugging slow operations. Triggers on: latency, timing, performance, slow, speed, instrumentation.
Best use case
latency-tracker is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Per-call and aggregated latency tracking for MEV infrastructure. Use when implementing performance monitoring or debugging slow operations. Triggers on: latency, timing, performance, slow, speed, instrumentation.
Teams using latency-tracker should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/latency-tracker/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How latency-tracker Compares
| Feature / Agent | latency-tracker | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Per-call and aggregated latency tracking for MEV infrastructure. Use when implementing performance monitoring or debugging slow operations. Triggers on: latency, timing, performance, slow, speed, instrumentation.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Latency Tracker
Per-call and aggregated latency tracking for MEV infrastructure.
## When to Use
- Implementing performance monitoring
- Debugging slow operations
- Adding instrumentation to code paths
- Tracking end-to-end latency
- Setting up alerting thresholds
## Workflow
### Step 1: Define Span Hierarchy
Structure spans from e2e_flow down to individual calls.
### Step 2: Instrument Code
Wrap operations in tracker.span() calls.
### Step 3: Set Alert Thresholds
Configure alerts for latency exceeding expected ranges.
---
## Span Hierarchy
e2e_flow (root)
├── rust_hotpath_call (5-15ms)
│ └── rpc_eth_call (5-20ms)
├── tx_submit
└── tx_confirm (1-15s)
## Usage
```typescript
const e2e = tracker.startE2E('liq');
await e2e.span('rust_call', async () => {
return await callRust();
});
e2e.complete({ success: true });
```
## Alert Thresholds
| Span | Expected | Alert |
|------|----------|-------|
| rust_hotpath | 5-15ms | >30ms |
| rpc_eth_call | 5-20ms | >50ms |
| e2e_to_submit | 10-50ms | >100ms |Related Skills
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