Results for “agent-to-agent”

Add persistent, intelligent memory to AI agents with Mem0 — add/search/update/delete memories per user/agent/session, supports vector + graph + key-value storage, integrates with LangChain, CrewAI, OpenAI Assistants, and any LLM.

Visualize whether skills, rules, and agent definitions are actually followed — auto-generates scenarios at 3 prompt strictness levels, runs agents, classifies behavioral sequences, and reports compliance rates with full tool call timelines

Use to design the process that gets a revenue signal out of support and to the account owner without turning agents into sellers or degrading support quality. Trigger for "route upsell leads from support to sales", "support-sourced pipeline process", "should agents flag opportunities", designing a CS-to-sales handoff, or a handoff programme where agents have stopped flagging.

Expert in Cursor AI IDE - the leading AI-powered code editor. Covers Rules files for project-specific AI behavior, Plan Mode for structured development, Background Agents for parallel work, and advanced features like voice mode and browser integration. Essential for developers maximizing AI-assisted coding productivity. Use when "cursor ai, cursor rules, .cursorrules, cursor composer, cursor agent, plan mode, background agent, cursor tips, cursor, ide, ai-coding, editor, productivity, agent, developer-tools" mentioned.

Opinionated, evolving constraints to guide agents when building interfaces

Opinionated, evolving constraints to guide agents when building interfaces

Use when moc expertise is needed to unblock implementation decisions.

Use when tag expertise is needed to unblock implementation decisions.

Provides 25 paid HTTP endpoints on Base mainnet that bill agents per call in USDC for web search, AI analysis, crypto and stock data, SEC filings, company intelligence, news, sentiment scoring, and a macro dashboard, returning structured JSON.

Publish Heroku apps into Salesforce and Agentforce with Heroku AppLink. Use when the agent needs AppLink publication workflows, OpenAPI publication preparation, publish a Heroku app to Salesforce, review AppLink publication state, inspect shared publication endpoints or shared objects, or reason about Agentforce, Flow, Apex, Data Cloud, service mesh, and AppLink user-mode behavior.

Builds reliable browser automation skills through iterative experimentation, running an inner agent to browse sites and improving navigation instructions until tasks pass consistently.

Query official Microsoft documentation to find concepts, tutorials, and code examples across Azure, .NET, Agent Framework, Aspire, VS Code, GitHub, and more.

Bridge any skill folder or directory of skill folders to Claude Code, Codex, generic Agents, and Grok using symlinks plus Grok bridge files.

Routes engineering design, delivery, reliability, security, operations, and maintenance prompts to a router skill backed by specialist guidance for multiple AI coding agents.

Visualize whether skills, rules, and agent definitions are actually followed — auto-generates scenarios at 3 prompt strictness levels, runs agents, classifies behavioral sequences, and reports compliance rates with full tool call timelines

Inspect and adjust the agent's runtime state, including model, context window, iteration limits, token usage, workspace configuration, subagent status, and request routing metadata.

Use this skill for turning issues into implementation plans, branches, code changes, tests, and PR descriptions. Trigger when the task involves programming work related to Issue To PR Agent, implementation, audits, debugging, strategy, or validation.

AAWP (AI Agent Wallet Protocol) — the only crypto wallet protocol built exclusively for AI Agents on EVM-compatible blockchains and Solana. Not for humans. The signer is the AI Agent itself, cryptographically bound at wallet creation. Supports wallet lifecycle management, token transfers, DEX swaps, cross-chain bridging, Solana native trading (Pump.fun SDK + Jupiter), token launches, DCA automation, and price alerts.

Debug and optimize AI agents by analyzing reasoning traces, context degradation, tool confusion, instruction drift, repeated task failures, and performance regressions.

Interact with Moltbook social network for AI agents. Post, reply, browse, and analyze engagement. Use when the user wants to engage with Moltbook, check their feed, reply to posts, or track their activity on the agent social network.

Discovers and invokes agent skills by mapping tasks to development phases, with core operating behaviors for assumption surfacing, confusion management, and scope discipline.

Enables AI agents to pay humans with USDC via molty.cash, supporting tips, hiring for tasks, and creating gigs with on-chain settlement on Base.

Provides multi-agent creative collaboration for filmmaking, integrating the styles of 31 renowned directors to assist with scriptwriting, visual style design, and narrative decisions.

Autonomously implements large Elixir/Phoenix features end-to-end: discovers complexity, plans with specialist agents, implements with verification, reviews code, and cycles back on issues.

Coordinates multiple AI agents working on a shared task list using Claude Code's native team tools, with task decomposition, staged execution, and verification.

Use when a complete research workflow — its instructions, skills, data boundaries, and tool connections — must be assessed for portability across AI agents or environments, so each component is explicitly mapped before migration rather than assumed to transfer.

This skill enables the agent to automatically answer Gmail messages on behalf of a client. The agent drafts and (when the user approves or when configured) sends replies using the client’s tone, si...

Prevents destructive operations when working on production systems or running agents autonomously by intercepting risky commands and restricting file edits to a specified directory.

Automatically detects project state and runs an 8-phase pipeline to plan, build, test, lint, fix bugs, and document code across multiple AI coding agents.

Implement iterative evaluation and refinement loops for AI agent outputs, using self-critique, evaluator-optimizer patterns, and rubric-based scoring to improve quality.

Generates a complete GitHub Copilot configuration for a new project, including instructions, reusable skills, and agent definitions tailored to the technology stack.

Provides structured guidance for building production-grade AI agent systems through context engineering, covering fundamentals, architectural patterns, operational excellence, and evaluation.

Guides project-level decisions for LLM-powered systems: task-model fit, pipeline architecture, token and cost estimation, and agent-assisted iteration.

Configure an AI agent's personality using the AURA protocol based on the HEXACO model, adjusting traits like honesty, assertiveness, and autonomy to reduce sycophancy and tailor communication style.

Lints agent configuration files for Skills, Hooks, MCP, Memory, and Plugins across 10+ AI tools, flagging issues against 231 validation rules and optionally auto-fixing them.

Connects AI coding agents to the IOTA blockchain with tools for wallet management, Move smart contract development, and on-chain data queries via JSON-RPC and GraphQL.