openactors
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TDQS
Scored across 26 tools
Tools are grouped into clear clusters—actors, runs, tasks, datasets, schedules, and job tracking—and each tool targets a distinct resource and action. A few pairs like call-actor vs run-actor-task and mark-job vs record-response are somewhat close, but their descriptions clearly separate them.
Most tools follow a lowercase hyphenated verb-noun pattern, which is readable and mostly predictable. There are minor inconsistencies such as fetch vs get, call vs run, clean-up vs delete, and list naming varies (get-actor-run-list vs get-actor-task vs get-schedules).
At 26 tools, the set is over the 25-tool threshold and feels heavy for an agent to navigate. The actor, dataset, schedule, and job-tracking concerns are broad enough that the server may be trying to cover too much in one surface.
The set covers actor discovery, execution, run inspection, saved tasks, datasets, schedules, storage access, and job follow-up workflows with no obvious dead ends. Minor gaps exist: key-value store access is read-only and there is no individual dataset deletion, though clean-up-storage partially covers cleanup.