Results for “osisoft-pi”

Install, configure, and extend Pi, a terminal coding harness, with support for custom providers, models, extensions, skills, packages, themes, SDK integration, RPC mode, JSON event streams, and ecosystem packages for subagent delegation, MCP servers, interactive forms, and web access.

Install the Holoscan SDK Python wheel via pip into a virtual environment and verify with example scripts.

Write, review, debug, and test Python FastAPI applications with path operations, dependencies, Pydantic models, lifespan, middleware, background tasks, exception handling, and ASGI tests.

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

Post-process AI-generated text through the unslop CLI to strip AI writing patterns before publishing

DSPy: declarative LM programs, auto-optimize prompts, RAG.

Consume and produce STIX/TAXII 2.1 cyber threat intelligence feeds using Python, including server discovery, collection polling, object parsing, and SIEM/TIP integration.

DSPy: declarative LM programs, auto-optimize prompts, RAG.

Post-process AI-generated text through the unslop CLI to strip AI writing patterns before publishing

Post-process AI-generated text through the unslop CLI to strip AI writing patterns before publishing.

Reviews code using pi CLI with read-only tools. Delegates the review to pi (dev/pi) with a structured review rubric, running in read-only mode to prevent accidental edits. By default reviews uncommitted working tree changes (git diff HEAD) with pi restricted to the read tool; explicit targets (--branch/--diff/@file/PR) or --explore widen pi to read,grep,find,ls. Use when the user asks to "review code with pi", "pi review", "have pi review", "let pi review", or invokes /pi:review.

Automate OSINT collection using SpiderFoot REST API and CLI for target profiling, module-based reconnaissance, and structured result analysis across 200+ data sources.

Install and configure Pi-hole as a network-wide DNS ad blocker on a Raspberry Pi or Linux host, manage blocklists, set up DNS-over-HTTPS, integrate DHCP, create local DNS records, and troubleshoot DNS issues.

Post-process AI-generated text through the unslop CLI to strip AI writing patterns before publishing

Post-process AI-generated text through the unslop CLI to strip AI writing patterns before publishing

Create, enrich, and share threat intelligence events on a MISP platform using PyMISP, including IOC management, feed integration, STIX export, and community sharing workflows.

Post-process AI-generated text through the unslop CLI to strip AI writing patterns before publishing

Build industrial-grade SCADA/HMI dashboards in MATLAB following industrial-HMI conventions (ISA-101-aligned): gray-field philosophy, alarms at source, write safeguards, fixed-range trends, drill-down layout. Produces a real App Designer app (.mlapp, or plain-text .m+.xml on R2026b+) by handing serialization to the matlab-build-app skill when available, and falls back to a programmatic .m app otherwise. Use when wrapping OPC UA / Modbus / MQTT / OSI PI / PI AF monitoring scripts into a live operator app, building plant overviews, designing operator dashboards, or any time a user asks for a "SCADA dashboard", "HMI", "plant dashboard", "operator screen", or "industrial monitoring app" in MATLAB. Trigger on: SCADA, HMI, industrial dashboard, plant overview, operator screen, uigauge, uilamp, alarm banner, gray-field, ISA-101, OPC UA dashboard, setpoint, write safeguards, alarm visualization, OSIsoft PI, AVEVA PI, PI Server, PI Data Archive, PI AF, PI Asset Framework, piclient, afclient.

DSPy: declarative LM programs, auto-optimize prompts, RAG.

Guides the user through configuring pi — provider, model, base URL, and API key. Use when the user asks to "setup pi", "configure pi", "pi setup", "set up pi provider", "pi config", "change pi model", or invokes /pi:setup. Only run this skill when the user explicitly requests pi setup — never auto-invoke.

Post-process AI-generated text through the unslop CLI to strip AI writing patterns before publishing

DSPy: declarative LM programs, auto-optimize prompts, RAG.

Diseña y optimiza pipelines de CI/CD para GitHub Actions y GitLab CI, incluyendo automatización de tests, linting, builds y deploys.

Run MISP, curate threat feeds, and auto-generate detections for Wazuh, Sigma, and Suricata.

Fix PyPI package name collisions when local package name exists on PyPI

Post-process AI-generated text through the unslop CLI to strip AI writing patterns before publishing

Programs ESP32 microcontrollers in C/C++ or MicroPython. Use for IoT projects with WiFi/Bluetooth.

Deploy MISP, configure threat feeds, use the PyMISP API for programmatic access, and build automated collection pipelines that aggregate IOCs from multiple community and commercial sources.

Build, run, and visualize multi-step AI generation workflows by chaining image, video, and audio nodes into automated pipelines.

Supply-chain malware infection scanner. IoC-based local scan + safe eradication for npm/PyPI worm campaigns (Mini Shai-Hulud 1st/2nd, S1ngularity, lottie-player). Detects OS persistence (LaunchAgent/systemd), IDE-hook implants (.claude/.vscode/.github/workflows), lockfile-pinned malicious versions, and known C2/Session-Protocol exfil traces. Orchestrates credential rotation in the correct order so revocation does not trigger the `rm -rf ~/` retaliation payload. Don't use for static SAST (Sentinel), skill/MCP/`.claude/` supply-chain audit (Chain), Sigma/YARA rule authoring (Vigil), or incident coordination (Triage).

Development with Mpi: tools and best practices

Post-process AI-generated text through the unslop CLI to strip AI writing patterns before publishing.

Read, write, and modify DICOM medical imaging files, including pixel data extraction, anonymization, format conversion, and compression handling.

Fine-tune and serve Physical Intelligence OpenPI models (pi0, pi0-fast, pi0.5) using JAX or PyTorch backends for robot policy inference across ALOHA, DROID, and LIBERO environments. Use when adapting pi0 models to custom datasets, converting JAX checkpoints to PyTorch, running policy inference servers, or debugging norm stats and GPU memory issues.