Results for “optical-inspection”

Applied Optics Design Skill

Applied Optics Modeling Skill

Perform vulnerability scanning in OT/ICS environments safely using passive monitoring, native protocol queries, and carefully controlled active scanning with Tenable OT Security to identify vulnerabilities without disrupting industrial processes or crashing legacy controllers.

Advanced Optics Modeling Skill

Conduct comprehensive security assessments of Operational Technology (OT) networks including SCADA systems, DCS architectures, and industrial control system communication paths, addressing the Purdue Reference Model layers and identifying IT/OT convergence risks.

Open-Vocabulary Object Detection Using Captions

Authorized OT/ICS security assessment covering Purdue model zoning, PLC/SCADA exposure, industrial protocol discovery, and safe passive-first evaluation.

Advanced Optics Design Skill

Perform intermediate-level optics design tasks including wave equation solving, behavior prediction, and physical modeling for research, industry, or education.

Run Comet's Opik — open-source LLM observability, evaluation, and optimization — from one routing-first skill: install the Python/TypeScript SDK, stand up a server (Comet.com cloud, Docker Compose via `./opik.sh`, or Kubernetes/Helm), wire tracing through `@opik.track` or one of 50+ framework integrations (OpenAI, Anthropic, LangChain, LangGraph, LlamaIndex, CrewAI, DSPy, Ollama, Bedrock, Vercel AI SDK, …), score outputs with LLM-as-a-judge metrics (Hallucination, Moderation, Answer Relevance, Context Precision), and run Datasets/Experiments evaluations including PyTest CI gates. Use when the user wants LLM tracing, prompt evaluation, production LLM monitoring, agent optimization, or guardrails with Opik. Triggers on: opik, comet opik, opik configure, opik.sh, llm observability, llm tracing, llm as a judge, hallucination metric, prompt evaluation, opik dashboard, opik guardrails, agent optimizer.

Diagnose OCI Functions setup, control-plane, deployment, invocation, and observability issues using a deterministic triage workflow.

Import object detection models from HuggingFace or NVIDIA NGC into a DeepStream pipeline with automated ONNX download, TensorRT engine build, custom parser, multi-stream benchmark, and PDF report generation.

Fine-tune and deploy CLIP vision-language models for zero-shot classification, image-text retrieval, and embedding extraction with ONNX and TensorRT support.

Trains, evaluates, exports, quantizes, and runs inference for Sparse4D multi-camera temporal 3D object detection and tracking models using TAO.

Trains, evaluates, and runs inference for BEVFusion multi-sensor 3D object detection models that fuse LiDAR and camera data in bird's-eye-view space for autonomous driving.

Skill for the Observability area of paddock. 105 symbols across 26 files.

Collects publicly available information about a target organization to identify attack surfaces, social engineering targets, technology stacks, and credential exposures for authorized security testing.

Standard reviewer for correctness and reproducibility. Use when the user asks to talk to Omen, requests a code review, or needs reproducibility verification.

Performs security scanning, compliance checks, deployment planning, and infrastructure setup, with optional dependency auditing and bundle size analysis.

Computer vision engineering skill for object detection, image segmentation, and visual AI systems. Covers CNN and Vision Transformer architectures, YOLO/Faster R-CNN/DETR detection, Mask R-CNN/SAM segmentation, and production deployment with ONNX/TensorRT. Includes PyTorch, torchvision, Ultralytics, Detectron2, and MMDetection frameworks. Use when building detection pipelines, training custom models, optimizing inference, or deploying vision systems.

Cross-runtime 2-stage pipeline for Claude Code, Codex/OMX, and Gemini/Antigravity/OMA: trace causal hypotheses, inject evidence into deep-interview style requirements crystallization, then hand off to the right runtime planner/executor.

Use this when the system needs logging, metrics, tracing, alerting, or operator-visible runtime signals for APIs, workers, integrations, serverless functions, or local-to-production supportability.

Executes Atomic Red Team tests mapped to MITRE ATT&CK techniques, performs coverage gap analysis, and runs detection validation loops to measure blue team visibility.

SRE and Observability Audit

CI security scanning: secrets, deps, SAST, triage, expiring exceptions

Deploy Nozomi Networks Guardian sensors for passive OT network traffic analysis to achieve asset visibility, threat detection, and vulnerability assessment across industrial control systems.

Access microscopy images and metadata via the OMERO Python API: retrieve datasets, analyze pixels, manage ROIs and annotations, and batch-process for high-content screening workflows.

Monitors Modbus TCP traffic on SCADA and ICS networks to detect anomalous function code usage, unauthorized register writes, and suspicious communication patterns using deep packet inspection with pymodbus, Scapy, and Zeek.

Nocaps: Novel Object Captioning at Scale

Systematic Obsidian vault audit and normalization — structure, frontmatter, wikilinks, broken links, Git hygiene.

COCO: Microsoft COCO: Common Objects in Context

Audits source code for observability gaps — missing telemetry, poor observability practices, and code structure that resists instrumentation — then emits a ranked, bounded finding list. Invoke when the user says "observablip this", "observablip `pkg/foo`", "audit observability", "review telemetry", "find missing spans", "audit o11y on this PR", "review my logging", or "is this instrumented well enough?". Read-only; never edits files.

Observability and reliability engineer — SLOs, alerting, instrumentation, and incident response.

OPS-only dev-mode visual API binding for React/Next.js or static HTML UI elements and REST endpoints.

Adds logging, metrics, tracing, and alerting to make production behavior visible and diagnosable.