Results for “eval”

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.

Use when evaluating the free energy (kcal/mol) of an RNA secondary structure, calculating co-folding energies for two RNA strands, or analyzing consensus structures from multiple sequence alignments.

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.

Generate tests, design test strategies, and ensure code quality through testing. Use when writing tests, improving test coverage, designing test infrastructure, or evaluating test quality.

Dataset analysis and data quality specialist. Use when the user asks to talk to Cypher, requests the data detective, or needs dataset assessment, bias analysis, and benchmark evaluation.

Build durable backend AI agents with the eve framework. Use when creating, editing, or debugging an eve project — agent instructions, skills, tools, connections, channels, sandboxes, subagents, schedules, or evals.

Python design patterns including KISS, Separation of Concerns, Single Responsibility, and composition over inheritance. Use when making architecture decisions, refactoring code structure, or evaluating when abstractions are appropriate.

Identify skill coverage gaps and improvement opportunities. Use when analyzing missing skills for a task, creating skill gap issues, evaluating skill effectiveness, or refining skill progressive disclosure.

Perform a PESTLE analysis covering Political, Economic, Social, Technological, Legal, and Environmental factors. Use when assessing the macro environment, doing strategic planning, or evaluating external factors affecting your business.

Use this skill when creating a new Claude skill from scratch, editing or improving an existing skill, or measuring skill performance with evals and benchmarks. Invoke whenever the user says things like 'make a skill for X', 'turn this workflow into a skill', 'test my skill', 'improve my skill', 'run evals', 'benchmark this', or 'optimize my skill description'. Also use proactively when the conversation has produced a repeatable workflow that would benefit from being captured as a skill. Covers the full lifecycle: capture intent, draft SKILL.md, run evals, review with user, iterate, optimize description, package. NOT for general coding help, debugging runtime errors, building MCP servers, writing Claude hooks, or creating plugins - use domain-specific skills for those.

Build AI applications using the Azure AI Projects SDK for TypeScript, managing agents, connections, deployments, datasets, indexes, and evaluations.

Categorize, evaluate, and prioritize customer feature requests against product goals using strategic alignment, impact, effort, and risk analysis.

Evaluate and improve interface usability using heuristic analysis based on Nielsen's 10 heuristics, Krug's laws, and severity ratings.

Evaluate an AI product idea across outcomes, hypotheses, risks, and positioning to decide whether it deserves investment or recommendation.

Design click and first-click tests to evaluate navigation clarity and information findability in user interfaces.

Runs a five-phase pipeline—evaluation, specification, implementation, review, and QA—to build a feature end-to-end with specialized agents.

Computes CIDEr and related metrics to score how well generated image descriptions align with human consensus, using reference sentences and triplet annotations.

Adversarial robustness and ML safety specialist. Use when the user asks to talk to Viper, requests the adversary, or needs failure mode analysis, attack surface review, and robustness evaluation.

This skill should be used when the user asks to "analyze competitors", "assess competitive landscape", "identify differentiation", "evaluate market positioning", "apply Porter's Five Forces", or requests competitive strategy analysis.

CONDOR v2.0 — Multi-Asset Thesis Picker. Evaluates BTC, ETH, SOL, HYPE simultaneously and enters the strongest thesis. Conviction-scaled margin. DSL exit managed by plugin runtime via runtime.yaml.

Use this skill when selecting an MRO for drug testing program oversight. Covers MRO qualifications under Part 40, what the MRO does, and how to evaluate MRO services.

Use when evaluating competitors, market positioning, or assessing competitive threats. This skill provides a structured framework for analyzing competitors' offerings, strategies, and market positioning to inform strategic decisions.

Generate an Ansoff Matrix analysis mapping growth strategies across market penetration, market development, product development, and diversification. Use when considering growth options, planning market expansion, or evaluating strategic growth paths.

Trains, evaluates, exports, and runs inference for person re-identification models using TAO, learning discriminative embeddings for cross-camera matching.

Fine-tune a TAO model with standard supervised training, evaluation, and export, with AutoML bypass and platform-specific credential intake.

Train, evaluate, export, and run inference for pose classification models using ST-GCN on skeleton keypoint sequences.

Fine-tune LLMs using LoRA, QLoRA, and PEFT with Hugging Face, including dataset preparation, hyperparameter tuning, evaluation, and deployment.

Guides production AI systems: RAG pipelines, embeddings, vector databases, fine-tuning, prompt engineering, cost estimation, quality evals, and caching.

Guides production LLM operations: RAG pipelines, embeddings, vector databases, fine-tuning, prompt engineering, cost estimation, quality evals, and AI architectures.

Systematically evaluates alternatives against weighted criteria, builds a comparison matrix, and recommends the best option with documented rationale and trade-offs.

Turns model work into a production ML system with data contracts, reproducible training, quality gates, deployable artifacts, and monitoring.

Evaluates a containerized framework for deploying distributed big data workloads, measuring execution time and cloud cost scaling from four to eight nodes.

A skill to evaluate how secure Firestore security rules are. Use this when Firestore security rules are updated to ensure that the generated rules are extremely secure and robust.

Evaluate Agent Skill design quality against official specifications and best practices. Use when reviewing, auditing, or improving SKILL.md files and skill packages. Provides multi-dimensional scoring and actionable improvement suggestions.

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.

Design a structured protocol for auditing AI-generated text against Ennis's six CT standards. Use when students need to critically evaluate AI output in any subject.