Analytics & Monitoring Agent Skills for Grok Build

Compact Snakemake workflow patterns. Keep rules short, complex logic in Python modules.

Social media monitoring, narrative tracking, and open-source intelligence for journalists.

Route a goal through acc's scored-memory loop via acc_act(runtime="solve"); deliberate any returned brain_frame and submit via continue.

Use when hardening the reproducibility of a SOSP paper's results before submission — pinning the OS-level environment, recording hardware…

Performance profiling principles. Measurement, analysis, and optimization techniques.

Manage unified memory and thermals during long-running ML jobs on NVIDIA DGX Spark.

Preflight and diagnose the ten known failure modes for ML training on NVIDIA DGX Spark.

Use when the exhibits of a Journal of Urban Economics (JUE) manuscript must make the spatial pattern visible — maps, event-study plots…

Expert speech-language pathologist specializing in AI-powered speech therapy, phoneme analysis, articulation visualization, voice…

Bring declared user journeys within pre-declared performance budgets, proven by measurement.

Use when designing or diagnosing how an LLM application assembles, renders, mutates, retrieves, caches, evicts, or compacts model-visible…

Operate the SpikingJelly package for SNN modeling, datasets,

Knowledge base from \"Spinning Up in Deep RL\" by Joshua Achiam (OpenAI, MIT-licensed).

Use when writing, reading, or debugging SPIP logs — spip_log(), journal(),

Master data visualization with chart selection, dashboard design, Tableau, Power BI, and effective data storytelling.

This skill enables Claude to split datasets into training, validation, and testing sets.

Use when tasks involve creating, editing, analyzing, or formatting spreadsheets (`.xlsx`, `.csv`, `.tsv`) with formula-aware workflows…

Use when tasks involve creating, editing, analyzing, or formatting spreadsheets (`.xlsx`, `.csv`, `.tsv`) using Python (`openpyxl`…

SRE-focused reasoning for analyzing incidents, writing postmortems, and performing root-cause and causal analysis.

Guided statistical analysis for research data - test selection, assumption checking, effect sizes, power analysis, Bayesian alternatives…

Run hypothesis tests, analyze A/B experiment results, calculate sample sizes, and interpret statistical significance with effect sizes.