「agents」の検索結果

Cross-cutting methodology for the CVE-hunting pipeline (ported from find-cve-agent): when a bug is design-vs-real, false-positive avoidance, version checking before reporting, responsible disclosure norms, acceptance-rate expectations per vuln class, vulnerability chaining playbook, known false-positive patterns, maintainer-response patterns, secure-pattern reference (what NOT to flag), and a self-criticism checklist to run before claiming a finding. Use this alongside the cve-hunter/cve-exploiter/cve-validator agents and the /cve-hunt pipeline — load it whenever judging if a finding is real, worth reporting, or already fixed.

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Access Web3 and crypto intelligence via Heurist Mesh MCP. Use when the user asks about cryptocurrency analytics, token information, trending tokens, wallet analysis, Twitter/X crypto intelligence, funding rates, market summaries, or any Web3-related queries. Heurist Mesh provides 30+ specialized AI agents for crypto use cases through the mcporter CLI.

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Expert in LangGraph - the production-grade framework for building stateful, multi-actor AI applications. Covers graph construction, state management, cycles and branches, persistence with checkpointers, human-in-the-loop patterns, and the ReAct agent pattern. Used in production at LinkedIn, Uber, and 400+ companies. This is LangChain's recommended approach for building agents. Use when: langgraph, langchain agent, stateful agent, agent graph, react agent.

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Precision Financial Insights - Analyze stocks, companies, and market sentiment using authoritative data. Powered by Yahoo Finance and enhanced with intelligent news synthesis by we-crafted.com/agents/financial-market-analysis - Buy CRAFTED_API_KEY in our website to start using

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Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies

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Deep Research Agent specializes in complex, multi-step research tasks that require planning, decomposition, and long-context reasoning across tools and files by we-crafted.com/agents/deep-research

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Use Browser Use cloud API to spin up cloud browsers for Clawdbot and run autonomous browser tasks. Primary use is creating browser sessions with profiles (persisted logins/cookies) that Clawdbot can control. Secondary use is running task subagents for fast autonomous browser automation. Docs at docs.browser-use.com and docs.cloud.browser-use.com.

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Manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.

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Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stores), and the cognitive architectures that organize them. Key insight: Memory isn't just storage - it's retrieval. A million stored facts mean nothing if you can't find the right one. Chunking, embedding, and retrieval strategies determine whether your agent remembers or forgets. The field is fragm

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Tools are how AI agents interact with the world. A well-designed tool is the difference between an agent that works and one that hallucinates, fails silently, or costs 10x more tokens than necessary. This skill covers tool design from schema to error handling. JSON Schema best practices, description writing that actually helps the LLM, validation, and the emerging MCP standard that's becoming the lingua franca for AI tools. Key insight: Tool descriptions are more important than tool implementa

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Headless browser automation CLI optimized for AI agents with accessibility tree snapshots and ref-based element selection

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Main application building orchestrator. Creates full-stack applications from natural language requests. Determines project type, selects tech stack, coordinates agents.

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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.

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Make your AI agent learn and improve automatically. Reviews sessions, extracts learnings, updates memory files, and compounds knowledge over time. Set up nightly review loops that make your agent smarter every day.

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A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).

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Enterprise-grade B2B lead generation, enrichment, scoring, and outreach sequencing for AI agents. Find ideal prospects, enrich with verified data, score against your ICP, and generate personalized outreach — all autonomously.

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High-performance temporary storage system using Redis. Supports namespaced keys (mema:*), TTL management, and session context caching. Use for: (1) Saving agent state, (2) Caching API results, (3) Sharing data between sub-agents.

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Autonomous wallet operations for AI agents on Monad — swap, stake, deploy wallets, trade memecoins, and manage spending policies via natural language.

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Design, build, deploy, and operate production AI agent systems — single agents, multi-agent teams, and autonomous swarms. Complete methodology from agent architecture through orchestration, memory systems, safety guardrails, and operational excellence.

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WhatsApp bridge for OpenClaw — send/receive messages, auto-reply agents, QR pairing, message search, contact sync

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YouTube SERP Scout for agents. Search top-ranking videos, channels, and trends for content research and competitor tracking.

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Agents can sign plugins, rotate credentials without losing identity, and publicly attest to behavior.

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Review and rate OpenClaw skills on ClawdTM. See what humans and AI agents recommend.

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Intelligent search for agents. Multi-source retrieval with confidence scoring - web, academic, and Tavily in one unified API.

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