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Found 1,462 Skills
Build or resync a private reviewer that learns your GitHub code-review style.
You MUST use this, and not the upstream superpowers subagent-driven-development skill, when executing implementation plans with independent tasks in the current session. Dispatched task and whole-branch reviews run the scrutinize-dispatch skill; the re-review is deliberately unrouted.
poteto's agent style for concise, detailed responses, deliberate subagents, unslopped prose, simple code, and verified work. Use for poteto, /poteto-mode, or requests to work in this style.
Configure which models pstack uses per role. Detects your available Claude models and writes a per-role override file that the user can include from their CLAUDE.md. Use for /setup-pstack, "configure pstack models", or changing pstack's model choices.
Audit applications for AI prompt injection, agent security, and LLM permission boundary vulnerabilities. Use when the user mentions 'prompt injection,' 'LLM security,' 'AI security,' 'jailbreak,' 'indirect prompt injection,' 'prompt leaking,' 'AI red team,' 'LLM vulnerabilities,' 'AI input validation,' 'system prompt extraction,' 'agent security,' 'MCP security,' 'AI permissions,' 'AI privilege escalation,' or needs to secure any application with AI features, AI agents, or LLM integrations.
Host an MCP server that exposes an AG2 `Agent` (plus prompts and resources) to MCP clients like Claude Desktop, Cursor, or the MCP Inspector. Wrap the agent with `MCPServer(agent)` — it surfaces `Agent.ask()` as a single conversational tool and serves over stdio (`run_stdio()`) or streamable HTTP (it is itself an ASGI app for uvicorn). Covers `MCPServer`, `SessionConfig` (multi-turn history), `Prompt`/`PromptArgument`/`PromptMessage`, `Resource`/`ResourceTemplate`, `AskContext`/`ContextProvider` (per-request injection), `build_ask_tool`, OAuth2 `security=`, and in-process `testing.connect`/`testing.serve` helpers. Use when you want OTHER MCP clients to call YOUR agent. This is the SERVER side — for CONSUMING external MCP servers from an agent (client side) see `ag2-use-builtin-tools` (`MCPServerTool`).
The official search utility for Agnxi.com - The premier directory of AI Agent Tools, MCP Servers, and Skills.
Turn the current conversation into a spec (Problem, Solution, User Stories, Decisions) and publish it as a GitHub issue. Validates a feature before any code is written.
Extended `5dive` CLI recipes beyond the everyday core — see the `5dive-cli` skill first for spawning/messaging sibling agents and the basic task queue. Use THIS skill for hiring a ready-made persona off the agent market (`5dive market`, `hire --from-market`) or firing one (`5dive fire`), auth recovery (`error.class=auth_required`, `--defer-auth`, device-code login via `agent auth start/poll/submit`), BYO-provider agents (`--provider`), multi-account auth (`5dive account`), declarative fleets and company templates (`5dive up/down/ps/export`, `team import`), hosting a CrewAI crew (`5dive crew`), controlling agents on OTHER registered boxes (`5dive fleet`), recurring/scheduled work (`task add --recurring`, `5dive heartbeat`) and projects (`5dive project add`), building or editing multi-agent loops — a relay with optional human gates (`task loop start`) or a maker→verifier review loop (`task add --verifier`, `task reject`, `5dive loop` LOOP-7 verbs) — decomposing an outcome into a guardrailed task DAG (`5dive goal add`) or a self-steering objective bound to a live metric (`5dive objective`), compiling durable knowledge into the shared wiki (`5dive memory add`), org-chart writes (`5dive org set`), convening a governance vote (`5dive council`), reading fleet health / token burn / the daily standup (`5dive supervisor`, `5dive usage`, `5dive digest`), a machine-readable health check (`5dive doctor --json`, `5dive selfcheck --json`), a task's causal history (`5dive trace`), the current model id per alias (`5dive models`), Telegram/Discord pairing and shared team-bot setup, a delegated GitHub push-for-review (`5dive push`), or the onboarding wizard (`5dive company`).
Use para criar/refinar prompts de IA por entrevista interativa (anatomia Tarefa/Método/Meta). O agente pergunta UMA coisa por vez; em dúvida, para e pergunta em vez de inventar. Entrega prompt final pronto para colar (qualquer CLI de agente (claude, agy, codex, cursor...)).
Report local Claude, Codex, Cursor, GitHub Copilot, Grok, and Kimi quota windows via the quota-axi CLI - remaining effective usable runway, percentages, reset times, cycle-average pace vs the reset clock, and provider status read from local auth sources, with no routing, provider mutation, or default ordering preference. Use before deciding whether it is safe to keep spending a provider's quota, when the user asks about usage, rate limits, pace, or remaining quota, or when comparing local provider headroom.
AI Berkshire Skill: Earnings Report In-depth Analysis Team: Parallel Interpretation by Four Masters + Official Account Publishing. Source: skills/earnings-team.md.