overscore-cli
ovs, the command line for Overscore: query your data, build and deploy Python models,
send results to the systems your team works in, from a terminal or from a coding agent like Claude Code.
uv tool install overscore-cli # or: pip install overscore-cli
export OVERSCORE_KEY=ovs_... # from Settings > Keys in Overscore
ovs init --dataset sales # this folder becomes a project: overscore.toml, the rules and skills for your agent
ovs guide # every command
ovs init --for claude|codex|cursor|gemini|agents|all writes the rules and skills in your agent's layout
(CLAUDE.md and .claude/skills, AGENTS.md, .cursor/rules, GEMINI.md).
A Python model, start to finish
ovs pull sales.leads # a sample, for local runs
# write models/lead_scores/model.py and model.toml
ovs model run lead_scores --local # runs here, on the sample
ovs upload put lead_model files/lead_model.pkl # the fitted model it reads
ovs model push lead_scores # saved and run in Overscore; prints the run's log
ovs destination add webhook "Their CRM" https://crm.example.com/in
ovs sync add scores_out --from lead_scores --key lead_id --to "Their CRM"
ovs sync run scores_out
A model's script imports its helper: from overscore_model import rows, read, file, output, log.
The folder as a checkout
ovs pull # every model, saved query, metric and dashboard as files: models/, saved_queries/, metrics/, dashboards/
ovs status # what changed here since the pull, what changed in Overscore, what is new on either side
ovs push # every changed file back, each push a version; "pull first" when it changed in Overscore since the pull
Every command prints JSON when its output is not a terminal ({"success": true, ...}, or
{"success": false, "error": "..."} with exit code 1), so agents can read it.
1 maintainer
Metadata
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Release files for overscore-cli 0.1.8
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