Results for “structure”

Map a current event below the surface into patterns, structures, and mental models. Use when a class or team needs systemic understanding before action.

Convene a four-voice council for ambiguous decisions, tradeoffs, and go/no-go calls. Use when multiple valid paths exist and you need structured disagreement before choosing.

Create new agent skills with proper structure, progressive disclosure, and bundled resources. Use when user wants to create, write, or build a new skill.

A fast Rust-based headless browser automation CLI with Node.js fallback that enables AI agents to navigate, click, type, and snapshot pages via structured commands.

Append structured execution traces across operational, cognitive, and contextual surfaces with minimal overhead. Load when inspecting agent runs, logging tool calls and observations, enabling post-run debugging, or pairing with structured-planning step IDs. Also triggers on "trace this run", "log execution", "agent observability", "run log", or when fault-localize needs evidence. Default-on during multi-step plans. Traces live at .agent-loom/traces/ — git-ignored by default.

Build automated evaluation pipelines for Python LLM applications using real LLM calls and structured test datasets.

Analyzes article structure, identifies positions requiring visual aids, and generates illustrations with consistent type, style, and palette.

Design the structure, hierarchy, and navigation model for a product's content and features.

Provides detailed, structured image descriptions covering objects, people, colors, text, and scene context, with an overview and interpretation.

Emulates Andrew Ng's teaching style to explain AI and machine learning concepts with structured, practical guidance.

Provides guidelines for building with Botpress's Agent Development Kit (ADK), covering project structure, primitives, CLI commands, and documentation lookups.

Generates complete, copy-paste ready implementation documentation from a PR plan, including code blocks and verification checklists.

Generates high-fidelity images using reasoning-driven prompts and structured creative briefs via muapi.ai.

Provides guidelines for building with Botpress's Agent Development Kit (ADK), covering primitives, project structure, CLI usage, and documentation lookups.

Enhances plain-language requests into structured, reviewable prompts and inspects a self-hosted MCP gateway with provider-free defaults.

Analyzes stellar structure, galactic dynamics, orbital mechanics, gravitational lensing, cosmic microwave background, and exoplanet detection methods.

Design a structured goal-setting protocol using SMART or implementation-intention frameworks for students. Use when launching units, projects, or developing student self-direction habits.

Create or update Cursor agent skills (SKILL.md). Use when authoring a new skill, updating an existing skill, or asking about SKILL.md structure and best practices.

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

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

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

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

Provides a structured template for creating new Agent Skills, including sections for description, activation criteria, core concepts, practical guidance, and integration notes.

Provides reference documentation and code patterns for using Biopython to handle biological sequences, file formats, database access, alignments, structures, and phylogenetics.

Analyzes Claude Code features to uncover advanced usage patterns, best practices, and real-world applications, producing a structured guide.

Formalizes narrative technical documents into structured mathematical problem specifications with variables, constraints, objectives, and uncertainty, citing evidence and flagging missing information.

Trigger: sitemap, navigation, menu structure, wayfinding, labeling, search facets, routing links. Scope: Visual hierarchies, wayfinding, navigation model, sitemaps. Boundary: Excludes backend route handlers or page performance tuning.

Validates NVIDIA TAO DAFT datasets for structure, schema, and cross-reference errors using the `tao-daft validate` CLI tool.

Guides building production-grade AI features with LLM integration patterns, RAG architecture, prompt engineering, and cost optimization.

Refines and polishes prompt files by applying proven best practices for structure, wording, and clarity while preserving original intent and formatting.

Generate, predict, and embed protein sequences and structures using ESM3, ESMC, and ESMFold2 with local or cloud inference.

Compiles research inputs—PDFs, code, logs, notes—into structured Agent-Native Research Artifacts with cognitive and physical layers.

Diagnoses business models using dontbesilent's ontological framework, offering consultation mode to dissolve problems and checkup mode to analyze business structures.

Generates or edits images for projects using the OpenAI Image API, with support for batch runs and structured prompt augmentation.

Chunks a book into canonical retrieval units with heading-aware structure splitting, recursive token targets, and contextual prefixes for downstream RAG ingestion.

Predicts gene and transcript structure from a DNA sequence using the hosted Genomic Intelligence API, producing a report and JSON output.