Results for “ironscales”

High-fidelity ASCII/Braille rendering via the Risomorphism-1911 pipeline — edge-aware downsampling, presets, quality gates, and eikon mirror workflows

Compute the F1Score metric using torchmetrics when predictions and ground-truth labels are available.

Computes the AUROC metric using torchmetrics, handling binary, multiclass, and multilabel tasks with configurable thresholds and averaging.

Upscale and enhance image and video resolution using AI

Guides setting up Drizzle ORM with Vercel Postgres and Vercel KV for a manufacturing analysis app, covering schema definition, queries, migrations, caching, sessions, and rate limiting.

Fast DataFrame library (Apache Arrow). Select, filter, group_by, joins, lazy evaluation, CSV/Parquet I/O, expression API, for high-performance data analysis workflows.

Computes the InfoLM metric from torchmetrics for evaluating text generation against ground truth, with configurable information measures and sentence-level scoring.

Provides guidance for enterprise-grade RL training using miles, a production-ready fork of slime. Use when training large MoE models with FP8/INT4, needing train-inference alignment, or requiring speculative RL for maximum throughput.

Manages vector embeddings with Pinecone for semantic search, recommendation, and RAG pipelines.

Computes the Receiver Operating Characteristic (ROC) metric using torchmetrics, supporting binary, multiclass, and multilabel tasks.

Write, review, debug, test, and optimize Python Polars code with version-grounded object types, schemas, and execution boundaries.

Statistical modeling toolkit. OLS, GLM, logistic, ARIMA, time series, hypothesis tests, diagnostics, AIC/BIC, for rigorous statistical inference and econometric analysis.

Review PostgreSQL code for best practices, anti-patterns, and quality standards including JSONB, arrays, custom types, schema design, functions, and security features like Row Level Security.

Interprets Culture Index survey data, behavioral profiles, and personality assessments from JSON or PDF. Supports individual profile interpretation, team composition analysis, burnout detection, hiring profiles, manager coaching, interview transcript analysis, and conflict mediation.

Instrument LLM applications with OpenInference tracing for Phoenix AI observability, covering setup, custom spans, and production deployment.

Develop and implement OT-specific incident response playbooks aligned with SANS PICERL framework, IEC 62443, and NIST SP 800-82 that address unique ICS challenges including safety-critical systems, limited downtime tolerance, and coordination between IT SOC, OT engineering, and plant operations teams.

Upscale and enhance images using Real-ESRGAN, Thera, FLUX Upscaler, and Topaz via the inference.sh CLI.

Provides guidance for enterprise-grade RL training using miles, a production-ready fork of slime. Use when training large MoE models with FP8/INT4, needing train-inference alignment, or requiring speculative RL for maximum throughput.

Computes the R2Score metric using torchmetrics, handling single and multi-output predictions with options for adjusted and variance-weighted scores.

Covering Indexes

Fast DataFrame library (Apache Arrow). Select, filter, group_by, joins, lazy evaluation, CSV/Parquet I/O, expression API, for high-performance data analysis workflows.

PASS/FAIL eval rubrics and alignment loops for Sid Orchestra (global). Use when the user says sid evals, @sid-evals, grade this, eval gate, alignment score, or wants to stop AI slop. Works in any workspace; bootstraps EVALS.md from ~/.cursor/skills/sid-orchestra/templates if missing.

Upscale and enhance image and video resolution using AI

Perform high-performance genomic interval operations and bioinformatics file I/O on Polars DataFrames, including overlap, nearest, merge, coverage, complement, subtract, and reading/writing BED, VCF, BAM, GFF, FASTA, and FASTQ formats with streaming and cloud-native support.

Query Belgian railway (NMBS/SNCB) schedules via the irail CLI.

Automates multi-source enrichment of IPs, domains, URLs, and file hashes using VirusTotal, AbuseIPDB, Shodan, GreyNoise, URLScan.io, and MISP to provide contextual risk scoring and disposition recommendations for SOC analysts.

Write efficient PostgreSQL queries and design schemas with proper indexing and patterns.

Compute the Equal Error Rate (EER) metric using torchmetrics for binary, multiclass, or multilabel classification tasks, with reference signatures and usage examples.

Creates modular typography scales with size, weight, and line-height relationships for consistent digital interfaces.

Read and query onchain data using events, The Graph, Dune, Ponder, Multicall3, and WebSocket subscriptions, with guidance on block iteration limitations.

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Compute the Kruskal-Wallis H-test using scipy.stats.kruskal for independent samples, returning the H statistic and p-value.

Tracks indicators of compromise from initial discovery through validation, enrichment, deployment, monitoring, and retirement to maintain a high-quality, actionable indicator database.

Downloads, exports, and inspects existing Arize traces and spans to understand what an LLM app is doing or debug runtime issues. Covers exporting traces by ID, spans by ID, sessions by ID, and root-cause investigation using the ax CLI. Use when the user wants to look at existing trace data, see what their LLM app is doing, export traces, download spans, investigate errors, or analyze behavior regressions.

Reference guide to 9 prioritization frameworks with formulas, when-to-use guidance, and templates — RICE, ICE, Kano, MoSCoW, Opportunity Score, and more.