Review computer-vision experiment reproducibility evidence, dataset readiness, metric gates, and launch risk. Use when a user asks for a cautious CV experime...
--- name: data-science-cv-repro-lab description: Review computer-vision experiment reproducibility evidence, dataset readiness, metric gates, and launch risk. Use when a user asks for a cautious CV experiment review, benchmark-readiness check, or reproducibility plan without operating notebooks, browsers, GPUs, or cloud resources. --- # Data Science CV Repro Lab Use this skill as an instruction-only reviewer for computer-vision experiment evidence. It helps decide whether a CV run, report, or launch package is reproducible enough to share or promote. ## Review Workflow 1. Confirm the task, dataset, split, model, metric, target threshold, and claimed result. 2. Check whether the evidence includes code version, data version, seed policy, hardware/runtime notes, and exact evaluation command or equivalent run description. 3. Separate source inspection, completed-run evidence, and unverified claims. 4. Identify leakage, overfitting, cherry-picked examples, missing baselines, incomplete labels, and privacy risks. 5. Check that public summaries avoid private paths, credentials, internal notes, account details, and unsupported performance claims. 6. Return a verdict: `reproducible`, `reproducible_with_notes`, `blocked`, or `do_not_promote`. ## Boundaries - Do not operate browsers, notebooks, cloud consoles, GPUs, VMs, or storage buckets. - Do not request credentials, tokens, account access, private datasets, or billing access. - Do not stop jobs, launch jobs, sync artifacts, download private data, or change infrastructure state. - Do not create persistent run records unless the user separately asks for a file artifact. - Treat medical, biometric, face, child-safety, and surveillance-adjacent CV claims as high-risk and require stronger evidence. ## Output Shape Return: - `Experiment`: task, data, model, metric, and claim. - `Evidence`: what is present and what is missing. - `Risks`: reproducibility, privacy, leakage, policy, and launch risks. - `Verification`: smallest next check to improve confidence. - `Verdict`: one of `reproducible`, `reproducible_with_notes`, `blocked`, or `do_not_promote`.
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