Sample scorecard

Larkmail

Transactional email

Across 162 recommendation probes and the build journeys below, agents break the build with Larkmail 47% of the time they touch it, and pick Mailspire instead. The leak is the first install and the first build, not retention.

Prepared byAgentRank
DataIllustrative sample, synthetic figures
ModelsClaude + Codex, split throughout

Scorecard

A 0-100 composite of the four metrics, with its confidence band. Larkmail scores 64 (Strong) but sits #3 in the category, and build success is what holds the score down: 53%, the worst of its four numbers.

dashboard.agentrankhq.com
AgentRank Score, the agent funnel, and the biggest leak for Larkmail
The scorecard: the 0-100 AgentRank Score with its 95% band, the four metrics, and the biggest leak.

By model

The story changes with the model your customers run. Larkmail builds 70% on Opus but only 31% on Sonnet: a 39-point gap on the cheaper model that drives the most volume. A blended number would hide all of it.

dashboard.agentrankhq.com
Per-model comparison: Opus vs Sonnet across the full funnel, with sample sizes
Every metric split by model, with sample sizes and the n≥30 reportability gate.

What to fix

We read every failing run and isolate the cause (outdated docs, a type mismatch, a silent hand-roll), then rank the fixes by the score they'd recover. It reads like a plan, not a log; every fix links to the runs that prove it.

dashboard.agentrankhq.com
Prioritized fixes, each with projected score uplift and the failing-run evidence
Fixes ranked by projected uplift. Each drills into the actual failing runs behind it.

Competition

Who agents reach for when they pass over Larkmail, named, and by how much. The install is lost to Mailspire most often, with Postroute and self-hosted SMTP close behind. You know exactly who you're losing to.

dashboard.agentrankhq.com
The competitive leaderboard and the switch graph: who agents pick instead
Who agents recommend, install, and switch to instead. Named, in the category.

This is a sample on an illustrative tool. Yours uses your live data, named and private. Aggregate numbers are public; your per-tool numbers never are.

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