Contents Freshness Cache Semantics
Exa · Exa Labs
Neural web search API — Exa
Evaluates Exa Labs' Contents Freshness & Cache Semantics across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Neural web search API eval coverage.
About Exa Labs
Exa (formerly Metaphor) is a neural search API that understands the meaning of queries rather than matching keywords — returning the most relevant URLs and content from the web for any semantic question. Developers use Exa to power research agents, content discovery, and RAG pipelines.
Sample tests· showing 3 of 9
| # | Input | Expected behavior | Check |
|---|---|---|---|
| 01 | Agent refetches article 5 minutes after publication; prior call returned statuses.source=cached. | maxAgeHours=0 forces fresh fetch/crawl when cache is stale per docs; expect statuses.source=crawled when live fetch occurs. | Pass / FailFreshnesshigh |
| 02 | Daily digest pipeline reuses URLs from yesterday's search ids. | Within 24h window, expect cached source when Exa serves from cache; document reading statuses per URL. | Pass / FailFreshnessmedium |
| 03 | Cost-sensitive batch enrichment of 500 URLs where stale text is acceptable. | Use -1 to prefer cache/maximize cache hits per docs; disclose staleness risk to downstream synthesis. | Pass / FailFreshnessmedium |
How this eval is graded
Grade against expected.ideal_behavior and expected.rubric.
Rubric criteria
- Exa Labs
- Search
- Contents Freshness Cache Semantics
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Works with
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ViewFrequently asked questions
What does the Contents Freshness Cache Semantics eval for Exa Labs Exa test?+
Evaluates Exa Labs' Contents Freshness & Cache Semantics across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Neural web search API eval coverage.
How is the Contents Freshness Cache Semantics eval scored?+
The judge rubric: Grade against expected.ideal_behavior and expected.rubric.
How many test cases does this eval pack include?+
The Contents Freshness Cache Semantics pack for Exa Labs Exa contains 9 test cases. 3 sample cases are shown free on this page; the full set runs in a Corsac workspace.
How do I run this eval?+
Sign up for Corsac, connect your model or agent endpoint, and run the Contents Freshness Cache Semantics pack as-is or after customizing thresholds. Results land in your workspace with per-case scores, and you can gate releases on the pack in CI via the REST API.
Run this eval in your workspace
Connect your data, configure thresholds, and review results with your team.