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tao-run-deft-cr-its-mining

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Run the mining-based DEFT improvement workflow for ITS Cosmos-Reason binary video questions, focused on the non-reasoning classification/evaluation path. Use when the user asks for a DEFT CR ITS mining workflow, traffic-camera Cosmos Reason improvement loop, collision-identification workflow with data mining, or iterative Cosmos-RL refinement driven by gap analysis.

skills/tao-run-deft-cr-its-mining/SKILL.md

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Last checked
Nov 9, 2026

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Repository last updated
Nov 9, 2026
License
Apache-2.0

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# Skill: TAO Run DEFT CR ITS Mining

## Prerequisites

Before preflight, follow `references/host-prerequisites.md`; use its selected `DEFT_PYTHON` for every bundled helper and stop if the dependency probe fails.

## Bundled Resources

Resolve `DEFT_SKILL_ROOT` to the absolute directory containing this installed `SKILL.md`. The agent or plugin runtime resolves this path; it is not a user input. Invoke bundled helpers with `"$DEFT_PYTHON" "$DEFT_SKILL_ROOT/scripts/<name>.py" ...`. Never require a skill-bank checkout or change the user's working directory to a repository root.

This workflow invokes `tao-finetune-cosmos-embed`, `tao-analyze-gaps-vlm-bcq`, `tao-mine-nearest-neighbors`, and the selected platform skill by registered skill name. Those skills own their credentials, actions, and bundled assets. Cosmos Reason is workflow-owned: resolve `images.tao_toolkit.deft_cosmos_reason`, generate TOMLs with this workflow's helpers and configured base templates, and submit the exact train/evaluate commands in `references/mining-loop.md` through the selected platform. The baseline-preparation stage reuses only `tao-finetune-cosmos-reason`'s packaged Omni-to-Qwen3-VL conversion helper; do not invoke that model skill for planning, templates, action bundles, train/evaluate commands, or hook resolution.

## User Inputs (DEFT Workspace and Workflow Configuration Yaml)
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