Glossary
Rate Limiting
Controlling the frequency and volume of requests an AI agent can make to external services or the requests it will accept from users.
What is Rate Limiting?
Rate limiting protects both agents and the services they interact with from overload, abuse, and runaway behavior. Outbound rate limits prevent agents from overwhelming APIs, databases, or other resources, while inbound limits protect agents from denial-of-service attacks or unintentional overload. Limits are typically expressed as maximum requests per time window with different tiers for different users or use cases.
Effective rate limiting requires careful calibration to balance protection with functionality. Too-restrictive limits impair legitimate agent operations, while too-lenient limits fail to prevent abuse. Advanced implementations use dynamic rate limiting that adapts based on current system load, agent reputation, and request patterns.
Example
A research agent is rate-limited to 100 API calls per minute to external data sources. When analyzing a large dataset that would require 500 calls, the agent automatically spaces requests over 5 minutes, preventing API throttling while still completing the analysis efficiently.
How Signet addresses this
Signet considers rate limiting implementation as part of the Reliability dimension. Agents with well-tuned rate limits demonstrate operational maturity and respect for external resources, while agents that frequently hit rate limits or cause service disruptions may face score penalties.
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