Research Hub
AI-operable research workspace for Zotero, Obsidian, and NotebookLM. Use any two, or all three, through CLI, MCP, REST, and dashboard.
Codex Delegate
Delegates implementation-heavy or repetitive coding work (batch edits, boilerplate, multi-file refactors with clear patterns, test scaffolding) from Claude to OpenAI Codex CLI. Use when token cost outweighs judgment cost. Trigger phrases include "delegate to codex", "let codex do this", "batch refactor across files", "scaffold tests for". Avoid for architecture, security review, or root-cause deb…
Agent Debate
Use when a consequential decision needs adversarial review, opposing agent arguments, a second opinion via debate, or explicit trade-off analysis before implementation.
Agent Acceptance Gate
Use when a multi-agent round needs a pre-merge gate, pre-commit check, verification before push, or a PASS/FAIL decision after reconciliation.
Gemini Delegate
Delegates large-context reading, bilingual or Chinese (CJK / zh-TW) drafting, cross-file synthesis, and second-opinion review to Google Antigravity CLI (`agy`) or legacy Gemini CLI. Use when input exceeds Claude's working budget, when the user writes in Chinese, when terminology must align across long documents, or when a reviewer pass is needed. Trigger phrases include "summarize this in Chinese…
Agent Task Splitter
Use when the user asks to split a goal across Claude, Codex, or Gemini; plan a multi-agent run; break work into parallel agent tasks; or decompose a large task that needs bounded context handoffs. This is the **generic** multi-agent task splitter — writes `.coord/plan.yml` (a DAG) plus per-agent task files. NOT for research-domain routing that touches `.research/`, `.paper/`, or Zotero/Obsidian/N…
Awesome Agentic Ai Zh
A trilingual (繁中 / English / 简中) learning roadmap for agentic AI: from LLM basics to multi-agent systems, with 240+ curated resources and hands-on examples. 中文 AI agent 學習地圖。
Academic Writing Skills
End-to-end academic manuscript workflow for drafting, revision, reviewer response, figure-text consistency, claim-evidence audits, and pre-submission checks. Use this skill whenever a user asks for manuscript sections, paper revision, rebuttal letters, journal compliance, overclaim detection, GPT-style prose cleanup, figure captions, or evidence-backed academic writing. It is especially useful fo…
Agent Shared Memory
Use when the user asks to update shared memory, initialize multi-agent memory, summarize decisions so far, identify open questions, or prepare a fresh session primer.
Tool Calling Tutor
When the user is building a tool-calling agent and gets stuck — "為什麼 LLM 不呼叫我的 tool", "我這 schema 哪裡寫壞", "tool 被呼叫但 args 不對", "ReAct loop 跑不停", "the LLM won't call my tool", "help me design a function schema", "debug this tool-use behavior". Walks them through a 4-branch diagnostic + 5-step schema design walkthrough, with references to bad/good schema A/B and SDK-diff cheatsheet. Do NOT use for: p…
Agent Plan Act Reflect
Use when a task needs single-agent self-correction across multiple iterations — write plan, execute, critique own output, revise plan, re-execute, until convergence or budget exhausted. Different from `agent-debate` (which is 2 agents arguing pro vs con); this is 1 agent looping over its own work.
Agent Context Budget
Use when multi-agent work risks context overflow, memory growth, noisy logs, oversized handoffs, cross-session continuation, or parallel Codex and Gemini execution.
Agent Output Reconciler
Use when multiple agents have completed a round and the user asks to reconcile outputs, compare Codex and Gemini, synthesize run results, identify conflicts, or decide what should be retried.