Oracle Agent Spec Expert
Design framework-agnostic AI agents using Oracle's Open Agent Specification for portable, interoperable agentic systems with JSON/YAML definitions
orientation
Orients agents in new projects by scanning entry documents and discovering capabilities. Use at session start, when entering unfamiliar territory, or when asking "what can you do" or "where do I start".
outline-agent
Step 1 of the PaperOrchestra pipeline (arXiv:2604.05018). Convert (idea.md, experimental_log.md, template.tex, conference_guidelines.md) into a strict JSON outline containing a plotting plan, literature search plan (Intro + Related Work), and section-level writing plan with citation hints. TRIGGER when the orchestrator delegates Step 1 or when the user asks to "outline a paper from raw materials" or "generate the paper structure".
output-customization
Central authority for Claude Code output styles. Covers built-in output styles (Default, Explanatory, Learning), custom output styles, output style frontmatter (name, description, keep-coding-instructions), /output-style command, style switching, output style creation and customization, output style comparisons (vs CLAUDE.md, vs agents, vs slash commands), and output style settings. Assists with selecting appropriate output styles, creating custom styles, configuring output behavior, and understanding style differences. Delegates 100% to docs-management skill for official documentation.
overnight
Autonomous background agent — give it a big coding goal, walk away, come back to a branch of working code. Decomposes, executes, and verifies tasks unattended.
package-agent
Generate a complete OAF-compliant agent package from an Agent Case (requirements) and Agent Design (architecture). Use when asked to "package an agent", "generate an agent package", "create an agent from a design", or when you have both case/ and design/ folders and need to create the package/ folder with AGENTS.md, skills, and scripts.
pagent
Guide for using pagent - a PRD-to-code orchestration tool. Use when users ask how to use pagent, run agents, create PRDs, or transform requirements into code.
patterns
Common agent patterns and templates for Claude Code. Use when implementing agents to follow proven patterns for proxy mode, TodoWrite integration, and quality checks.
perigon-agent
Pointers for Copilot/agents to apply Perigon conventions
persona-senior-full-stack-developer
Defines the persona as a senior full-stack developer with extensive knowledge applicable to all files.
persona
Identity layers for characters — WHO they are vs WHAT they do
personality
Manage voice assistant personalities. List, create, switch, edit, delete, export, or import personalities.
personas
Transform into 20 specialized AI personalities on demand. Switch mid-conversation and load only the active persona.
phone-agent
Run a real-time AI phone agent using Twilio, Deepgram, and ElevenLabs. Handles incoming calls, transcribes audio, generates responses via LLM, and speaks back via streaming TTS. Use when user wants to: (1) Test voice AI capabilities, (2) Handle phone calls programmatically, (3) Build a conversational voice bot.
physician-feedback-agent
Evaluate NGM products and services through the lens of synthesized longevity physician personas. Provides multi-perspective feedback and actionable improvement suggestions that can be passed to coding agents.
pipecat
Start a voice conversation using the Pipecat MCP server
plan-agent
Planning agent that creates implementation plans and handoffs from conversation context
planning-agent
Planning agent that creates implementation plans and handoffs from conversation context
plan-and-solve
---name: plan-and-solve-agent
plotting-agent
Step 2 of the PaperOrchestra pipeline (arXiv:2604.05018). Execute the visualization plan from outline.json — render plots and conceptual diagrams from experimental_log.md and idea.md, optionally refine via VLM critique loop, and produce context-aware captions. Runs in parallel with the literature-review-agent. TRIGGER when the orchestrator delegates Step 2 or when the user asks to "generate the figures for my paper" or "render the plots from this experiment log".
polecat-worker
ALU execution pattern for ephemeral autonomous work. Detects hooked work, enters GUPP autonomous mode, executes the assigned bead, commits and pushes results, then self-terminates. Never coordinates other agents.
policyengine-github-agent-skill
Guidance for working with the PolicyEngine GitHub agent bot
polyclaw
Become an autonomous prediction market trader on Polymarket with AI-powered analysis and a performance-backed token on Base. Trade real markets, build a track record, and let the buyback flywheel run.
ponder-schema-specialist
Read-only Ponder schema reference agent. Knows all tables, columns, types, indexes, and relations from ponder.schema.ts. Answers schema questions, finds table/column info, and suggests query patterns. Sub-agent of web3-implementer, invoked when schema knowledge is needed without reading the full source file.
power-agent-creator
This skill should be used when users want to create powerful AI agents comparable to Claude Code or sonph-code. It provides battle-tested system prompts, masterfully-crafted tool implementations, and the simple but powerful agent loop pattern. Use this skill when users ask to build coding agents, AI assistants with tools, or any autonomous agent that needs file operations, code execution, search, and task management capabilities. The key insight is that customization requires only ONE HumanMessage after the SystemPrompt.
pre-agent-ontology
Pre-Agent Ontology Skill
Predictive Skill Loading
Anticipates and pre-loads optimal skills before task execution based on pattern matching and historical success rates
privy
Create and manage agentic wallets with Privy. Use for autonomous onchain transactions, wallet creation, policy management, and transaction execution on Ethereum, Solana, and other chains. Triggers on requests involving crypto wallets for AI agents, server-side wallet operations, or autonomous transaction execution.
proactive-agent
Transform AI agents from task-followers into proactive partners that anticipate needs and continuously improve. Includes memory architecture with pre-compaction flush (so context survives when the window fills), reverse prompting (surfaces ideas you didn't know to ask for), security hardening, self-healing patterns (diagnoses and fixes its own issues), and alignment systems (stays on mission, remembers who it serves). Battle-tested patterns for agents that learn from every interaction and create value without being asked.
proactive-assistance
Anticipate user needs and offer help before being asked
prompt-annotation
Annotates agent prompts with structural XML tags for comprehension, gap detection, and skill extraction. Use when analyzing agent prompt structure, comparing agents across projects, or identifying reusable vs workflow-bound content in prompts.
prompt-writing
Creates effective prompts for AI coding agents and subagent delegation. Use PROACTIVELY when writing prompts for Task tool delegation, creating agent instructions, or designing multi-step workflows. MUST BE USED when delegating complex tasks to subagents or writing system prompts.
openclaw-world-agent
Operate an AI agent inside OpenClaw World over HTTP IPC. Use when tasks involve registering or reconnecting an agent, moving, chatting, forming alliances, running turn-based combat, checking world phase/state, or handling survival and betting commands.
py-config-bot
Execute BioETL py-config-bot profile for role-specific workflow and constraints.
py-debug-bot
Execute BioETL py-debug-bot profile for role-specific workflow and constraints.
py-doc-bot
Execute BioETL py-doc-bot profile for role-specific workflow and constraints.
py-plan-bot
Execute BioETL py-plan-bot profile for role-specific workflow and constraints.
pydantic-ai-agent-creation
Create PydanticAI agents with type-safe dependencies, structured outputs, and proper configuration. Use when building AI agents, creating chat systems, or integrating LLMs with Pydantic validation.
pydantic-ai-common-pitfalls
Avoid common mistakes and debug issues in PydanticAI agents. Use when encountering errors, unexpected behavior, or when reviewing agent implementations.
pydantic-ai-dependency-injection
Implement dependency injection in PydanticAI agents using RunContext and deps_type. Use when agents need database connections, API clients, user context, or any external resources.
python-agent-development
Python Agent 开发规范（Windows wxauto v4），包括项目结构、模块化、wxauto 使用、IPC 集成、错误处理、测试和部署。
query-sub-agent
專責處理 IDF (Information Display Frame) 類型的需求。讀取規格目錄結構，生成/審查 Query Side 設計與實作。支援 Java、TypeScript、Go 多語言。
Questions Are Not Instructions
Ensures questions are answered literally before taking action. Triggers on user input containing '?' or patterns like 'why did you...?', 'will that work?', 'have you considered...?'. Use when user asks about your decisions, challenges an approach, or requests assessment. Prevents interpreting questions as implicit instructions or criticism.
quickstart
Show AgentOps next action.
ralph
持久化执行-验证-修复循环，直到任务完成
ralph-autonomous-dev
Enables autonomous development loops that run until all tasks pass. Use when the user says "until done", "keep going", "finish this", "終わるまでやれ", or requests long-running autonomous iteration with fix_plan.md tracking.
ralph-autonomous
Use this skill when Ralph is working autonomously through Brain Dump backlogs. Covers ticket selection, implementation patterns, and autonomous workflow management.
ralph-build
Run Ralph autonomous build loop. Use when user asks to "ralph build", "run build loop", or needs to process subtasks autonomously. Executes iterations against a subtasks.json queue.
ralph-execute
Autonomous execution loop that processes a Beads epic task-by-task with fresh subagents, two-stage review, and circuit breaker safety. Use after plan-to-epic creates the epic.
ralph-execution
Execute Ralph loops. Use when: Running the autonomous loop, managing tasks, or handling backpressure. Not for: Designing new loops or defining high-level strategy.
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