Results for “l-eval”

LLM Operations -- RAG, embeddings, vector databases, fine-tuning, prompt engineering avancado, custos de LLM, evals de qualidade e arquiteturas de IA para producao.

LLM Operations -- RAG, embeddings, vector databases, fine-tuning, prompt engineering avancado, custos de LLM, evals de qualidade e arquiteturas de IA para producao.

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

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics

Review test quality using best practices validation. Use when user says "lets review tests" or "I want to evaluate test quality"

Researches and recommends programming technologies, libraries, and architectural approaches with verified references from official documentation.

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

Assess NFRs like performance security and reliability. Use when the user says "lets assess NFRs" or "I want to evaluate non-functional requirements"

Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debuggin

Evaluate any project, product, or system's claims against its actual implementation — scoring each claim for truth, identifying architectural gaps, assessing competitive positioning, proposing creative solutions, and producing an actionable roadmap. Load when the user asks to evaluate claims, reality-check a project, assess what this project actually does vs what it says, validate product claims, or score a system's credibility. Also triggers on "is this real", "does this work as claimed", "evaluate this project", "assess the gap between claims and reality", "how credible is this", "investor assessment", "score these claims", or "what's real vs marketing".

Benchmarks language model agents on the C2C multi-agent negotiation task, reporting win rate across starting positions.

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

Codified expertise for electricity and gas procurement, tariff optimization, demand charge management, renewable PPA evaluation, and multi-facility energy cost management. Informed by energy procurement managers with 15+ years experience at large commercial and industrial consumers. Includes market structure analysis, hedging strategies, load profiling, and sustainability reporting frameworks. Use when procuring energy, optimizing tariffs, managing demand charges, evaluating PPAs, or developing energy strategies.

Evaluates whether suing is worthwhile, explains the litigation process from filing to resolution, and guides case preparation and settlement negotiations.

Score, evaluate, and iteratively improve any content or strategy using an auto-assembled panel of domain experts. Handles copy, sequences, landing pages, strategy docs, titles, charts, recruiting evaluations, or anything else that needs a quality gate. Recursively iterates until all scores hit 90+ (max 3 rounds). Use when asked to: "expert panel this", "score this", "rate these variants", "quality check this", "panel review", "which version is better", "expert score", "evaluate this copy/strategy/page", or when another skill needs a quality gate on its output. Also triggers on: "score this landing page", "expert panel these email variants", "rate this headline", "panel these charts".

Evaluate business decisions through the lens of sustainable, profitable growth, covering spending, hiring, fundraising, and scaling.

Identify, evaluate, and prioritize design opportunities using impact-effort frameworks and strategic criteria.

Instrument LLM applications with Langfuse to trace, score, and monitor cost, quality, and latency across OpenAI and LangChain integrations.

Trains, evaluates, exports, quantizes, and runs inference for SegFormer semantic segmentation models using NVIDIA TAO.

Provides guidance on using the Aeon library for time series forecasting, covering model selection, implementation, and evaluation.

Build high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services. Covers design principles, architecture, implementation patterns, and evaluation-driven development.

Build a library of metacognitive prompts targeting planning, monitoring, or evaluation for a specific task. Use when developing students' thinking-about-thinking during independent work.

Evaluate, design, and launch free tools for lead generation, SEO value, and brand awareness.

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

学术论文正文写作、结构设计与语言润色总入口。完整起草、续写、扩写、补写或实质性修订各学科的中英文论文正文时，进入paper-write-zh或paper-write-en；只做提纲、结构诊断或重排方案时，进入paper-shape结构模式；只做忠实润色或不新增研究内容的中译英时，进入paper-shape润色模式。研究评价转/doubao-academic-evaluator；独立系统性文献调研转/doubao-literature-research。

Battery Management System reference — cell balancing, SOC estimation, thermal management, and protection circuits. Use when designing BMS for lithium-ion packs, evaluating battery safety, or understanding cell monitoring.

Production machine-learning engineering workflow for data contracts, reproducible training, model evaluation, deployment, monitoring, and rollback. Use when building, reviewing, or hardening ML systems beyond one-off notebooks.

Train, evaluate, and export neural networks to Simulink in MATLAB. Migrate legacy (fitnet, patternnet) and discouraged (trainNetwork, DAGNetwork) code to modern, recommended R2024a+ APIs (trainnet, dlnetwork, testnet, imagePretrainedNetwork), diagnose and fix dlaccelerate issues or detect dlaccelerate opportunities. Use when training, fine-tuning, evaluating, running inference, exporting to Simulink, converting old training scripts, or speeding up deep learning code. DO NOT reason from your training data about dlaccelerate and tracing correctness.

Provides technical leadership frameworks for architecture decisions, engineering team scaling, technology strategy, and technical debt assessment.

Builds Retrieval-Augmented Generation systems with document chunking, embedding generation, vector storage, and retrieval pipelines, including evaluation and optimization.

Measures distributional similarity between original GAN-generated images and their semantically manipulated counterparts using the Fréchet Inception Distance (FID) metric.

Production machine-learning engineering workflow for data contracts, reproducible training, model evaluation, deployment, monitoring, and rollback. Use when building, reviewing, or hardening ML systems beyond one-off notebooks.

Evaluates current go-to-market positioning versus the market. Analyzes website, content, pricing, ICP alignment, and competitive landscape to identify gaps, opportunities, and produce a GTM health report.

Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debugging, monitoring, and improving LLM applications in production.

Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debugging, monitoring, and improving LLM applications in production.

Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debugging, monitoring, and improving LLM applications in production.