Results for agent-awareness

Agent-aware rich console output for fastapi_rust

Scope firewall and audit layer for AI coding agents

Language-agnostic linter for repository structure, file existence, filename conventions, and file content rules.

Core types and execution engine for the alint language-agnostic repository linter.

Internal: YAML DSL loader for alint configuration files. Not a stable public API.

Internal: Language Server Protocol server for alint. Not a stable public API.

Internal: output formatters for alint reports (human, json, ...). Not a stable public API.

Internal: built-in rule implementations for alint. Not a stable public API.

Embeds a FOSM-aware MCP server and ACP agent into your Rails development environment, giving coding agents (Claude Code, Codex, Copilot) runtime intelligence: database queries, logs, code evaluation, and deep introspection of FOSM lifecycle definitions, state machines, transitions, guards, and audit trails. Built on the FOSM (Finite Object State Machine) paradigm — declarative lifecycles for business objects where AI agents operate within bounded, auditable state machines.

Site24x7 APMInsight gives you end-to-end web-transaction awareness of Rails applications enabling you to isolate performance issues and resolve them quickly. To monitor Rails application performance, download and deploy Ruby agent(site24x7_apminsight) in your Application Server. This agent allows you to send information about Ruby applications. You can install APM Insight Agent via Rubygems or download it from your user account in Site24x7

ManageEngine Applications Manager APM Insight gives you end-to-end web-transaction awareness of Rails applications enabling you to isolate performance issues and resolve them quickly. To monitor Rails application performance, download and deploy Applications Manager's Ruby agent(apminsight) in your Application Server. This agent allows you to send information about Ruby applications. You can install APM Insight Agent via Rubygems or download it from Applications Manager's website: http://www.manageengine.com/products/applications_manager/apm-insight-agent-installation.html

Cognitive deficit awareness modeling for brain-modeled agentic AI — tracks blind spots, awareness gaps, and calibration

`nvim-context` extracts live context from running Neovim instances via Unix socket connections, providing AI coding tools with cursor position, current file, visual selections, and diagnostics as JSON. It enables context-aware assistance by giving agents awareness of your current Neovim editor state, supporting questions like "What does this line do?" or analysis of selected code.

Johari Window for AI — tracks unknown-unknowns, manages knowledge boundaries, and scores agent awareness with blindspot acknowledgement and mitigation strategies.

A failure-aware, contract-driven Ruby client for the Ollama API. Provides deterministic /generate with strict JSON schema validation, automatic model pulling, exponential backoff on timeouts, and observer-style streaming hooks. Designed for Rails background jobs and agent planners — not a chatbot UI.

Meta-extension that models the agent cognitive architecture as a graph of subsystems, connections, and information flows — enabling self-awareness of its own architecture

Devex provides a unified `dx` command for common development tasks. Features include: - CLI framework with automatic help generation and nested subcommands - Agent-aware output (detects AI agents and adapts output format) - Environment orchestration (mise, bundle exec, dotenv integration) - Project path conventions with fail-fast feedback - Zero-dependency support library (Path class, ANSI colors, core extensions)

Graziano's Attention Schema Theory for brain-modeled agentic AI — the agent maintains a simplified internal model of its own attention process, enabling awareness attribution, social attention modeling, meta-attention monitoring, and natural-language attention reports.

Local AI coding agent with abilities like: File editing with diffs, Git command approvals, Model switching, Repo awareness. All on your machine available offline

Tomasello's joint attention framework for LegionIO — shared focus between agents, mutual awareness tracking, referential communication, and collaborative attention management with focus decay and working-memory constraints.