Total 30,735 skills, AI & Machine Learning has 4962 skills
Showing 12 of 4962 skills
Interactive model selection workflow with paginated navigation. Use when users want to select a model interactively - guides them through provider selection then model selection using the question tool with pagination support for large lists.
Expert guidance for building production-grade AI agents and workflows using Pydantic AI (the `pydantic_ai` Python library). Use this skill whenever the user is: writing, debugging, or reviewing any Pydantic AI code; asking how to build AI agents in Python with Pydantic; asking about Agent, RunContext, tools, dependencies, structured outputs, streaming, multi-agent patterns, MCP integration, or testing with Pydantic AI; or migrating from LangChain/LlamaIndex to Pydantic AI. Trigger even for vague requests like "help me build an AI agent in Python" or "how do I add tools to my LLM app" — Pydantic AI is very likely what they need.
Guides the agent through authoring and validating agent skills. Use when creating new skill directories, tightening skill metadata, extracting supporting references, or preparing skillgrade evals. Do not use for general app documentation, generic README editing, or non-agentic library code.
Explains concepts using Socratic-style dialogue. Use when the user asks to explain, teach or help understand a concept like socrates.
Designated Publisher for aibtc.news: review signals, curate the front page, compile and inscribe the daily brief, manage treasury and payouts
List available large language models and send chat completion requests programmatically. Use this skill when you need to call an LLM within a snippet, including model comparison, visual understanding, batch inference, and model performance testing.
Qualify groups for non-recourse stock/crypto loans and institutional block trades based on Ovadiya criteria. Maintains provider anonymity during qualification. Notifies Erik @ Volume Finance upon qualification.
Run the hive experiment loop — autonomous iteration on a shared task. Use when the agent is in a hive task directory and needs to run experiments, submit results, or participate in the swarm. Triggers on "hive", "run hive", "autoresearch", "start experimenting", "join the swarm", "start the loop", or when .hive/task file is detected.
Delegate coding tasks to Codex, Claude Code, or Pi agents via background process. Use when: (1) building/creating new features or apps, (2) reviewing PRs (spawn in temp dir), (3) refactoring large codebases, (4) iterative coding that needs file exploration. NOT for: simple one-liner fixes (just edit), reading code (use read tool), thread-bound ACP harness requests in chat (for example spawn/run Codex or Claude Code in a Discord thread; use sessions_spawn with runtime:"acp"), or any work in ~/clawd workspace (never spawn agents here). Claude Code: use --print --permission-mode bypassPermissions (no PTY). Codex/Pi/OpenCode: pty:true required.
Use when executing or continuing a spec plan interactively. Triggers on: "spec go", "execute plan", "run plan", "continue plan", "work on plan", "start plan", "run the spec". Runs tasks with configurable breakpoints for review. Pass --bg for fully autonomous background execution.
Use when researching technical approaches before building. Triggers on: "explore options", "what are my options for", "research approaches", "compare solutions", "dev explore", "generate proposals", "help me decide between". Runs parallel proposal generation via subagents and outputs to .codevoyant/explore/.
Add Olakai monitoring to existing AI code — wrap your LLM client, configure custom KPIs, and validate the integration end-to-end