Emily2040

Emily2040/data-science-agent-skills

Skill Codex

Audit and package Jupyter notebooks for deterministic top-to-bottom execution across machines. Use when detecting out-of-order cell execution, hardcoded local paths, unseeded randomness, inline shell installs, or leaked secrets.

Emily2040/data-science-agent-skills

Skill Codex

Refactor exploratory Jupyter notebooks into modular, testable Python pipeline stages with explicit input/output contracts. Use when extracting data loading, feature engineering, training, and evaluation out of stateful notebook cells.

Emily2040/data-science-agent-skills

Skill Codex

Audit data science dependency manifests, pre-trained model weights, datasets, and licenses for security and reproducibility risks. Use when scanning requirements.txt, pyproject.toml, or environment files for unpinned packages and direct URL installs.

Emily2040/data-science-agent-skills

Skill Codex

Assess PII exposure, re-identification risk, and quasi-identifier linkage in analytics and ML datasets. Use when designing redaction, aggregation, k-anonymity, differential privacy, or clean-room controls before sharing or modeling sensitive data.

Emily2040/data-science-agent-skills

Skill Codex

Package prototype ML models into production engineering handoff bundles with input/output schemas, latency budgets, fallback baselines, and rollback triggers. Use when transitioning a validated model from data science exploration to ML engineering ownership.

Emily2040/data-science-agent-skills

Skill Codex

Reconstruct end-to-end table, file, column, and metric lineage across SQL queries, Python scripts, notebooks, and BI configs. Use when tracing upstream sources and downstream blast radius before refactoring pipelines or deprecating fields.

Emily2040/data-science-agent-skills

Skill Codex

Calculate minimum detectable effect (MDE), sample-size requirements, and events-per-variable ratios for small or rare-event datasets. Use when preventing underpowered experiments and overfitted models on scarce data.

Emily2040/data-science-agent-skills

Skill Codex

Translate technical data science findings into decision-grade executive memos with explicit asks, uncertainty intervals, and visible caveats. Use when converting notebooks, ablation tables, or experiment readouts into stakeholder recommendations.

Emily2040/rapid-domain-mastery

Skill Claude CodeCodex

Builds field maps from multi-source academic or technical corpora: expert mental models, debates, assumptions, prerequisites, oral-exam questions, and sprint study plans. Use for exam prep, research onboarding, or rapid topic mastery from multiple sources. Not for plain summaries or single short docs.

Emily2040/rapid-domain-mastery

Cursor rule Cursor

Use the rapid-domain-mastery workflow for source-heavy learning, literature onboarding, qualifying exam prep, and deep diagnostic tutoring.

Emily2040/rapid-domain-mastery

Agent Claude Code

Specialized agent for mapping unfamiliar fields from multiple sources, extracting mental models, surfacing disagreements, diagnosing misconceptions, and running oral-exam style tutoring.

Emily2040/parallel-codegen-orchestrator

Skill Claude CodeCodex

Plan, resume, verify, and safely parallelize substantial code work.