robo-harness
SO-101 arm workbench where a Jev decision runner picks bounded joint steps from typed candidate actions under a spend budget.
WHAT IT DECIDES
CHOICE
Picks one option from a fixed set
SCORE
Rates against ordered levels
NOUL
Answers a yes / no question
Inferred from this project's own one-line summary in the community list — it reads as a CHOICE decision. Read the source to confirm.
THE SHAPE OF A CHOICE CALL
A generic skeleton for this question type, not this project's actual code.
from typesafe import TypeSafe
ts = TypeSafe() # reads TYPESAFE_API_KEY
result = ts.evaluate(
state=page_state,
questions={
"next_action": {
"type": "choice",
"options": ["click", "scroll", "type", "done"],
"instructions": "What should the agent do next?",
}
},
)
action = result["next_action"] # the chosen option
confidence = result["next_action_confidence"]MORE IN Agent Decisions
Jev Ultrafastbrowser-use's ultrafast agent where Jev decides each next action and element to click, calling a language model only when text must be typed.fast-jev-compactionClaude Code plugin that replaces the compaction summary with Jev decisions, scoring every tool call and result for whether it is still needed instead of summarizing the session.jev-socialuses a Jev `Choice` at each step to select a concrete socai CLI operation and observed post or profile target on Instagram, TikTok, or LinkedIn, rejecting malformed or low-confidence decisions before execution.jev-agent-browsera parent agent delegates bounded tasks to a Jev loop that selects typed browser actions, validates them through agent-browser, and escalates ambiguity or stuck states back to the parent.