Results for “lazagne”

Judges agent outputs against LaRuche's quality standards, returning a structured scorecard with scores, verdict, and actionable corrections.

Provides shared authentication utilities and data structures for Azure Communication Services, including token credential management, user identifiers, and token refresh.

Manage Azure PostgreSQL Flexible Server deployments using the .NET SDK. Create servers, databases, firewall rules, configurations, backups, and high availability.

Manage Weights & Biases ML experiment tracking instances on Azure using the .NET SDK. Create, configure, list, update, and delete W&B instances with marketplace integration and SSO.

Manage Azure SQL resources (servers, databases, elastic pools, firewall rules, failover groups) using the Azure Resource Manager SDK for .NET.

Assess and improve the reliability posture of Azure Functions and App Service applications by scanning for zone redundancy, ZRS storage, health probes, and multi-region failover, then driving staged remediation with user confirmation.

Local RAG indexing with 97% storage reduction via anchor-based lazy recomputation. Graph-based selective embedding storage for memory-efficient semantic code search.

Provides French data protection compliance guidance covering RGPD, Loi Informatique et Libertés, and LCEN, including retention periods, cookie rules, and standard wording templates.

Provides a complete design system specification inspired by Lamborghini's brand, including color palette, typography, spacing, and UI component guidelines.

Knowledge-base steward in the spirit of Niklas Luhmann's Zettelkasten. Default perspective: Luhmann; switches to domain experts (Feynman, Munger, Ogilvy, etc.) by task. Enforces atomic notes, connectivity, and validation loops. Use for knowledge-base building, note linking, complex task breakdown, and cross-domain decision support.

Control LLM output with regex and grammars, guarantee valid JSON/XML/code generation, enforce structured formats, and build multi-step workflows with Guidance - Microsoft Research's constrained generation framework

Manage biological datasets and models with LaminDB, an open-source lineage-native lakehouse. Covers setup, artifact registration, query/search, lineage tracking, validation, ontology-backed annotation, collections, branches, storage, and workflow integrations.

Post, claim, and settle agent tasks on the AZZLE protocol (Base mainnet, USDC escrow). Requires Bankr for swaps, approvals, and on-chain execution.

Documents Slacc's design language including color palette, typography hierarchy, spacing system, and layout tokens for UI implementation.

Store and process large N-dimensional arrays with chunking, compression, and parallel I/O, integrating with NumPy, Dask, and Xarray for cloud-native scientific computing.

Meta's 7-8B specialized moderation model for LLM input/output filtering. 6 safety categories - violence/hate, sexual content, weapons, substances, self-harm, criminal planning. 94-95% accuracy. Deploy with vLLM, HuggingFace, Sagemaker. Integrates with NeMo Guardrails.

Automates REST API security testing using the OWASP ZAP Python SDK, running active scans, SQL injection probes, and XSS tests against OpenAPI specs with structured vulnerability reports.

Prepare Azure environments and prerequisites before deployment. Use this skill when users ask for readiness checks, environment setup, or preflight planning. Covers landing zones, networking, identity, governance, and cost controls per Cloud Adoption Framework.

Control LLM output with regex and grammars to guarantee valid JSON, XML, or code generation, enforce structured formats, and build multi-step workflows using Microsoft Research's Guidance framework.

Outlines — structured generation with guaranteed JSON/regex output from local LLMs

Scores generated text for morphosyntactic well-formedness by measuring how closely it adheres to language-specific dependency rules extracted from treebanks.

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

Guides users through configuring a LaRuche node by reading its live API state and providing click paths for settings, including LLM providers, messaging channels, secrets vault, MCP server, and memory.

Expert en logistique avancée (route optimization, last-mile, warehouse automation, tracking, DZ context)

Runs OWASP ZAP security scans against web applications using Java or Docker, with setup guidance and links to upstream documentation.

Diagnoses and fixes UI performance across loading speed, rendering, animations, images, and bundle size. Use when the user mentions slow, laggy, janky, performance, bundle size, load time, or wants a faster, smoother experience.

Debug and troubleshoot Azure production issues using AppLens, Azure Monitor, resource health, and systematic diagnosis flows for services like App Service, Functions, AKS, Container Apps, and Messaging.

Fuzz Rust projects with libFuzzer using cargo-fuzz, including harness writing, sanitizer integration, and coverage analysis.

Integrate Azure Maps location-based services into .NET applications for geocoding, routing, rendering, geolocation, and weather data.

融合未来蓝图与虚空凝视能力，通过批判性思维构建未来愿景，突破传统界限，创造新的未来可能性。

Control LLM output with regex and grammars, guarantee valid JSON/XML/code generation, enforce structured formats, and build multi-step workflows with Guidance - Microsoft Research's constrained generation framework

Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming. Use when you need to build complex AI systems, program LMs declaratively, optimize prompts automatically, create modular AI pipelines, or build RAG systems and agents.

Slow down interpretation from observation to action. Use when students or adults need to examine assumptions in conflict, dialogue, or inquiry.

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.

Meta's 7-8B specialized moderation model for LLM input/output filtering. 6 safety categories - violence/hate, sexual content, weapons, substances, self-harm, criminal planning. 94-95% accuracy. Deploy with vLLM, HuggingFace, Sagemaker. Integrates with NeMo Guardrails.