time-tracking-1-handle-rate-limits
Sub-skill of time-tracking: 1. Handle Rate Limits (+2).
Best use case
time-tracking-1-handle-rate-limits is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Sub-skill of time-tracking: 1. Handle Rate Limits (+2).
Teams using time-tracking-1-handle-rate-limits 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/1-handle-rate-limits/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How time-tracking-1-handle-rate-limits Compares
| Feature / Agent | time-tracking-1-handle-rate-limits | 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?
Sub-skill of time-tracking: 1. Handle Rate Limits (+2).
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
# 1. Handle Rate Limits (+2)
## 1. Handle Rate Limits
```python
import time
from functools import wraps
def rate_limited(max_per_second=1):
"""Rate limiting decorator."""
min_interval = 1.0 / max_per_second
last_call = [0.0]
def decorator(func):
@wraps(func)
def wrapper(*args, **kwargs):
elapsed = time.time() - last_call[0]
if elapsed < min_interval:
time.sleep(min_interval - elapsed)
result = func(*args, **kwargs)
last_call[0] = time.time()
return result
return wrapper
return decorator
```
## 2. Cache API Responses
```python
from functools import lru_cache
from datetime import datetime
@lru_cache(maxsize=100)
def get_projects_cached(workspace_id, cache_key=None):
"""Get projects with caching."""
return toggl.get_projects(workspace_id)
# Invalidate cache daily
cache_key = datetime.now().strftime("%Y-%m-%d")
projects = get_projects_cached(workspace_id, cache_key)
```
## 3. Validate Time Entries
```python
def validate_time_entry(entry):
"""Validate time entry before creating."""
if not entry.get("description"):
raise ValueError("Description is required")
duration = entry.get("duration", 0)
if duration > 12 * 3600: # More than 12 hours
raise ValueError("Duration exceeds 12 hours")
if duration < 60: # Less than 1 minute
raise ValueError("Duration too short")
return True
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