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Multi-layer memory architecture for agents: short-term context, long-term vector storage, and retrieval optimization. \n \n Covers seven memory types: short-term (context window), long-term (vector stores), working, episodic, semantic, and procedural memory, each suited to different information patterns \n Provides three core patterns: memory type selection, vector store choice, and chunking strategy to maximize retrieval accuracy \n Highlights critical retrieval challenges: contextual chunking,

Build, run, and debug iOS apps on a booted simulator with UI interaction and log capture. \n \n Discovers booted simulators, sets session defaults (project path, scheme, simulator ID), and builds/runs the current iOS project via XcodeBuildMCP tools \n Provides UI inspection ( describe_ui , screenshot ), interaction commands ( tap , type_text , gesture ), and element targeting by ID, label, or coordinates \n Captures simulator logs and console output with start/stop controls; includes build failu

Operational controls for long-lived agent workloads with observability, security, and lifecycle management. \n \n Covers four operational domains: runtime lifecycle (start, pause, stop, restart), observability (logs, metrics, traces), safety controls (scopes, permissions, kill switches), and change management (rollout, rollback, audit) \n Enforces baseline controls including immutable deployment artifacts, least-privilege credentials, environment-level secret injection, and hard timeouts with re

Fast Rust-based headless browser automation with real Chrome profile and session support. \n \n Supports headless Chromium, real Chrome with profile/OAuth reuse via Chrome DevTools Protocol, and persistent session cookies for logged-in workflows \n 30+ commands covering navigation, interaction (click, type, fill, drag, upload), extraction (text, HTML, attributes, screenshots), and state checks \n Deterministic element selection via snapshot refs (@e1, @e2, etc.) and semantic finders (role, text,

Memory management CLI for AI agents. Organize, search, and maintain your memory files.

Agents on Eve Horizon have no built-in "memory" primitive, but the platform provides storage systems at every timescale. This skill teaches how to compose them into coherent memory for agents that learn, remember, and share.

Create Agent Users in Microsoft Entra ID to enable AI agents to act as digital workers with user identity access. \n \n Provisions specialized user identities ( idtyp=user tokens) linked to agent identities, allowing agents to access user-only APIs like Exchange mailboxes, Teams, and org charts \n Requires a parent agent identity created from an agent identity blueprint; supports 1:1 relationship with optional manager assignment and license provisioning \n Includes step-by-step HTTP and PowerShe

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Declarative policies, intent classification, and audit trails for controlling AI agent tool access and behavior. \n \n Composable governance policies define allowed/blocked tools, content filters, rate limits, and approval requirements — stored as configuration, not code \n Semantic intent classification detects dangerous prompts (data exfiltration, privilege escalation, prompt injection) before tool execution using pattern-based signals \n Tool-level governance decorator enforces policies at fu

Automatically capture errors, corrections, and best practices to evolve agent capabilities safely over time. \n \n Records seven types of triggers (failures, user corrections, feature requests, API errors, knowledge gaps, better approaches, task reviews) into structured markdown files with deduplication to avoid low-value entries \n Promotes repeated patterns (≥3 occurrences) from learning logs into permanent capability files (AGENTS.md, TOOLS.md, SOUL.md) or extracts them as independent skills