How does this skill handle 429 'Too Many Requests' errors?

It implements exponential backoff with random jitter and automatically respects the 'Retry-After' header to resume requests at the earliest possible window without overwhelming the server.

Can I prioritize urgent medical queries over research tasks?

Yes, the skill includes a ClinicalRequestQueue that allows you to categorize requests as 'stat', 'urgent', 'routine', or 'research', each with dedicated concurrency and interval caps.

Is this compatible with the official OpenEvidence SDK?

Absolutely. This skill is designed to wrap around the standard SDK, providing an orchestration layer that handles reliability and traffic management automatically.

Does it support monitoring for DeepConsult credits?

Yes, it specifically tracks 'X-DeepConsult-Remaining' headers to provide real-time visibility into your remaining high-level clinical consultation quota.

OpenEvidence Rate Limiting

Name: OpenEvidence Rate Limiting
Author: jeremylongshore

byjeremylongshore

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1,538

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API Development

Manages API throughput and error handling for OpenEvidence clinical queries using advanced backoff and priority queuing.

The OpenEvidence Rate Limiting skill provides a robust framework for handling API quotas and 429 errors within clinical environments. It implements production-grade patterns such as exponential backoff with jitter, real-time rate limit header monitoring, and a unique clinical priority-based queuing system (STAT, Urgent, Routine, Research). This ensures that critical medical queries are prioritized and processed reliably while maintaining optimal throughput and staying within subscription tier limits.

Key Features

01Real-time monitoring of X-RateLimit and X-DeepConsult headers

02Exponential backoff with jitter for automatic 429 error recovery

03Adaptive throttling to maintain safety margins under heavy load

04Pre-configured rate limit tiers for Standard to Enterprise plans

051,538 GitHub stars

06Priority-based clinical request queuing (STAT/Urgent/Routine)

Use Cases

01Optimizing DeepConsult quota usage for high-value medical research tasks

02Managing concurrent clinical queries across different urgency levels in hospital integrations

03Building medical decision support systems that require 99.9% API reliability

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add jeremylongshore/claude-code-plugins-plus-skills openevidence-rate-limits

For use in Claude.ai and ChatGPT

Download Skill

Key Features

01Real-time monitoring of X-RateLimit and X-DeepConsult headers

02Exponential backoff with jitter for automatic 429 error recovery

03Adaptive throttling to maintain safety margins under heavy load

04Pre-configured rate limit tiers for Standard to Enterprise plans

051,538 GitHub stars

06Priority-based clinical request queuing (STAT/Urgent/Routine)

Use Cases

01Optimizing DeepConsult quota usage for high-value medical research tasks

02Managing concurrent clinical queries across different urgency levels in hospital integrations

03Building medical decision support systems that require 99.9% API reliability

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add jeremylongshore/claude-code-plugins-plus-skills openevidence-rate-limits

For use in Claude.ai and ChatGPT

Download Skill