Results for “severity-classification”

Classifies a patient's dizziness into one of four categories — vestibular/vertigo, presyncope, disequilibrium, or nonspecific — using history, timing, triggers, and associated symptoms. Use when a patient presents with dizziness, giddiness, lightheadedness, feeling off-balance, spinning, or nearly blacking out and you need to determine the type before further workup.

Alert design and on-call practices — severity, runbooks, SLO burn-rate alerting, escalation. Use when designing alerts, writing runbooks, reducing alert fatigue, setting up escalation policies, implementing SLO-based alerting, or improving on-call processes.

Responding to incidents: identifies impact scope, formulates recovery procedures, creates postmortems. Use when incident response or disaster recovery is needed. Delegates fixes to Builder.

Audits test code in any language using the academic testsmells.org 19-smell catalog, producing a severity-ranked report with specific locations and actionable fixes.

The single highest-leverage convention in code review is prefixing every comment

Hard Negative Mixing for Contrastive Learning

Use this skill when the user asks about FMCSA Compliance Safety Accountability (CSA) program scoring — the seven BASIC categories, BASIC Severity Indicator (BSI), peer percentiles, intervention thresholds, how violations age out, SMS Methodology, ISS (Inspection Selection System), what "alert" status means, Safety Measurement System mechanics, or DataQ disputes. Cite SMS Methodology v3.20.

Strengthen interfaces against edge cases, errors, internationalization issues, and real-world usage scenarios that break idealized designs.

Classify tasks by complexity and route heavy isolated coding work to Codex CLI with the correct current command syntax.

Practical bug triage and release-readiness judgment for Nick's projects. Use when grouping bugs by severity, deciding what to fix first, judging go/no-go for release, or turning messy bug lists into a prioritized action plan.

Analyzes code to separate essential complexity from incidental noise, then produces a ranked refactoring plan with a structural sketch and TRACE assessment, without making edits.

Strengthen interfaces against edge cases, errors, internationalization issues, and real-world usage scenarios that break idealized designs.

Scans C#/.NET code for ~50 performance anti-patterns across async, memory, strings, collections, LINQ, regex, serialization, and I/O with tiered severity classification.

Use this skill when the user asks about accident claims management — first-notice-of-loss procedures, working with insurance adjusters, claim severity classification, subrogation, claim closure timelines, and how to influence claim outcomes. Different from accident-investigation-playbook (which covers facts); this covers the insurance + claim side.

Curriculum Learning

Simulates a NeurIPS/SC/ICSE-style peer review with five reviewer personas (HPC, ML, Stats, Reproducibility, Devil's Advocate) that verify every claim against actual result data before submission.

Multi-dimensional lead qualification scoring. Evaluates leads against BANT criteria, firmographic fit, behavioral signals, and intent indicators. Outputs qualified/disqualified verdict with detailed reasoning.

Enforces complexity analysis, correct data structure selection, vectorization, and algorithm implementation discipline at principal-engineer level.

Provides a structured code review checklist covering security, performance, correctness, maintainability, testing, accessibility, and documentation, with a three-pass review process and guidance on severity levels and anti-patterns.

SVIT: Scaling up Visual Instruction Tuning