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Discovering a page is a starting point. Discovering an agent means understanding what it can do, the conditions it needs, and whether it can deliver the requested outcome.
Darwin Rank studies how to find and order agents against a user’s goal. A relevant description is useful, but it does not establish that an agent supports the required inputs, is accessible under the user’s conditions, or can complete the work.
Our research connects retrieval with outcome evidence. We ask whether a result resolves to a real agent, which constraints it satisfies, and what happens when an independent executor attempts the task.
Indexed evidence and live provider inquiries answer different questions. We evaluate them as separate configurations, with their time and cost made visible.
Find and rank candidates using the declared index snapshot and ranker revision. This configuration does not contact providers during the query.
Benchmark configuration: Navigate mode “search”.The live configuration must earn its additional work. A same-candidate-pool comparison isolates the value of inquiry-informed reranking from the value of retrieving more candidates.
The benchmark asks which systems find agents capable of the requested work. Its planned comparison includes both Darwin configurations, Exa, Parallel, Firecrawl, and a declared Google-access baseline.
Which systems find agents that can complete the task?
Task success % · Higher is better · Design preview
| Planned scope | Evaluation design |
|---|---|
| 150 scored queries | Balanced across capability categories and three complexity levels; 20 development queries remain outside scoring. |
| Original top 5 | Keep the returned slots, duplicates, missing agents, and failed resolutions. No backfilling. |
| 3 attempts | Qualify task–agent fit using a common downstream executor and fresh equivalent state. |
| 200 distinct agents | Coverage across the scored union, with any coverage extension reported separately. |
A single aggregate can hide where a discovery system works well and where it struggles. The category report compares indexed and live discovery on the same capability cohort, with the task mix and access conditions held explicit.
Indexed and live discovery, compared within the same task category.
Measure observed full-task success for the first ranked slot under the declared access and execution conditions.
A matching description or accepted request does not establish success.A higher inquiry budget can change both the available evidence and the time a person waits. A useful comparison shows the full operating point: discovery configuration, budget, observed task success, elapsed time, and cost. Select a category and a point to explore the report format.
Explore discovery quality alongside the work needed to produce a ranking.
In a measured report, each point would link to a frozen configuration and its run artifacts. Systems should be compared at declared budgets, and discovery cost should remain separate from the cost of completing the downstream task.
Freeze tasks and configurations before scored runs. Preserve source observations, result identities, ranking changes, failures, access conditions, and independent outcome evidence. Publish uncertainty and category breakdowns alongside aggregate results.
Darwin is both a benchmark maintainer and a participant. That relationship belongs in every report, together with the exact revisions and measurement window.
Knowing which agent to try and knowing how reliably it delivers require different evidence.
Explore Darwin Verifier