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Found 2,521 Skills
Native web workspace for Hermes Agent with chat, terminal, memory, skills, inspector, and multi-agent orchestration
AI-driven autonomous penetration testing with Kali Linux tools, multi-phase attack planning, and human approval gates for high-risk actions
Эксперт по оркестрации AI агентов. Используй для multi-agent systems, agent coordination, task delegation и agent workflows.
Design and implement autonomous AI marketing agent systems using the PRAL, BDI, and OODA frameworks. Invoke when a client is ready to move beyond reactive GenAI prompting to proactive, autonomous marketing workflows, or when planning an AI-first marketing operations architecture.
Build AI applications using the Azure AI Projects Python SDK (azure-ai-projects). Use when working with Foundry project clients, creating versioned agents with PromptAgentDefinition, running evaluations, managing connections/deployments/datasets/indexes, or using OpenAI-compatible clients. This is the high-level Foundry SDK - for low-level agent operations, use azure-ai-agents-python skill.
Use this skill when generating AI-agent-friendly documentation for a git repo or directory, answering questions about a codebase from existing docs, or incrementally updating documentation after code changes. Triggers on codedocs:generate, codedocs:ask, codedocs:update, "document this codebase", "generate docs for this repo", "what does this project do", "update the docs after my changes", or any task requiring structured codebase documentation that serves AI agents, developers, and new team members.
AI-agent readiness auditing for project documentation and workflows. Evaluates whether future Claude Code sessions can understand docs, execute workflows literally, and resume work effectively. Use when onboarding AI agents to a project or ensuring context continuity. Includes three specialized agents: context-auditor (AI-readability), workflow-validator (process executability), handoff-checker (session continuity). Use PROACTIVELY before handing off projects to other AI sessions or team members.
Skill for using Paperclip — open-source orchestration platform for running autonomous AI-agent companies with org charts, budgets, governance, and heartbeats.
Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for AI-agent, prompt-injection, MCP or toolchain, cloud, container, CI/CD, and supply-chain challenges. Use when the user asks to analyze prompt-to-tool flows, retrieval poisoning, mounted secrets, deployment drift, runtime-vs-manifest mismatches, registry provenance, or CI-produced artifacts under sandbox assumptions. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
Create and maintain an Obsidian-style graph memory bank in a code repository: small atomic Markdown nodes with YAML frontmatter, cross-links, explicit backlinks, and release/entity-driven coverage for fast AI-agent context retrieval. Use when asked to build/upgrade a 'memory bank', 'graph memory', 'obsidian docs', 'суперсвязанную графовую документацию', or when you need structured docs under docs/ that let an AI agent pull minimal but precise context.
Generate AI-agent-first CLIs from any API (OpenAPI, GraphQL, or browser-sniffed) with SQLite sync, compound commands, and MCP servers
Find, compare, adapt, and design repeatable AI-agent loops with explicit triggers, actions, verification, stopping conditions, guardrails, and handoffs. Use when a user asks for a loop, recurring agent workflow, automation cadence, iterative improvement process, an existing Loop Library recommendation, or help turning an outcome into a bounded copy-ready loop through a short question-led design session.