# Research Hub Multi AI > Research-domain router that writes `.coord/multi_ai_plan.md` when a single round of work will need two or more delegates AND the work touches research-hub artifacts (`.research/`, `.paper/`, Zotero/Obsidian/NotebookLM pipelines). For a single delegate, use `codex-delegate` or `gemini-delegate` directly — do not invoke this skill. For generic non-research multi-agent decomposition (pure code refactor, generic translation, no research-hub artifact), use `agent-collab-workspace:agent-task-splitter` instead (different artifact `.coord/plan.yml`, different scope). The router decides task splitting, dependency ordering, and reconciliation; the leaves execute. Use when this capability is needed. - Skill: `tomevault-io/research-hub-multi-ai` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/research-hub-multi-ai` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/research-hub-multi-ai/raw - Safety review: pending (external: skill-scanner PASS, skillspector PASS) - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: AI & ML - Author: tomevault-io (https://skillmd.com/u/tomevault-io) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tomevault-io/research-hub-multi-ai --- # research-hub Multi-AI Router This skill is the **router** in a router/leaves architecture. The leaves are `codex-delegate` and `gemini-delegate`. The router's only job is to write a coordination plan; the leaves read their assigned task brief from that plan and execute. ## When to Invoke Invoke this skill **only** when a single round of work will need two or more delegates. Examples: - Codex writes the test scaffolding **and** Gemini drafts the zh-TW companion doc — same round, both delegates. - Three parallel Codex runs against independent subtrees of the same repo, with a final Claude reconciliation step. - A sequence of mixed handoffs: Codex generates data, Gemini summarises in zh-TW, Codex writes a plot script. If only one delegate is needed this round, **use the leaf skill directly**. Do not produce a router plan for a one-task delegation — it adds ceremony with no benefit. ## When Not to Invoke - Single delegate this round (just Codex, just Gemini): use the leaf skill. - Single-LLM `research-hub auto` runs that pass `--llm-cli codex` or `--llm-cli gemini`: the flag is a research-hub feature, not a router decision. See "Single-LLM research-hub routing" below for reference. - Pure-Claude planning, review, or judgment work: keep it in Claude. ## Prerequisite check The router emits commands that go through the `research-hub` CLI in many cases. Before producing a plan, verify the CLI exists: ```bash research-hub doctor ``` If that command is **not found** (vs. emitting a health report), the user installed only the Claude Code marketplace plugin. Stop and tell them: > This skill orchestrates `research-hub` CLI commands across multiple AIs, but the CLI itself isn't installed. Please run: > > ```bash > pip install research-hub-pipeline > research-hub setup --persona researcher # or analyst | humanities | internal > ``` > > Then re-run your request. Do **not** produce a plan that calls `research-hub ...` if the CLI is missing — the user can't execute it. Plans that only call `codex-delegate` / `gemini-delegate` (no research-hub CLI) are fine without it. ## Output artifact: `.coord/multi_ai_plan.md` The router's only output is `.coord/multi_ai_plan.md` at the workspace root. Every plan has YAML frontmatter and a per-task brief block. Schema: ```yaml --- plan_id: # e.g. paper-corpus-2026-05 created_utc: 2026-05-09T12:34:56Z goal: success_criteria: - - tasks: - id: t1 agent: codex # codex | gemini | claude brief_path: .ai/codex_task_t1.md depends_on: [] success_criteria: - - id: t2 agent: gemini brief_path: .ai/gemini_task_t2.md depends_on: [t1] success_criteria: - risks: - --- ``` A ready-to-paste template lives in `references/multi_ai_plan_template.md`. The router writes the plan **and** writes each per-task brief at the path declared in `brief_path`. Leaves read the brief and execute. ## Hand-off contract The plan is the source of truth. After the router writes it: 1. Each leaf is invoked with the brief path as input. Leaves do not read the plan — they read their own brief. 2. Claude (or another reconciler) reads `result.json` from each leaf, compares against `success_criteria` in the plan, and decides accept / re-run / fall back. 3. Plans are append-mostly: if a re-run is needed, append a new task with a fresh id rather than mutating an existing one. ## Single-LLM research-hub routing (reference only) The `research-hub auto` command takes a `--llm-cli` flag to pick which CLI handles long mechanical work like crystal generation. This is a research-hub feature, not router logic. Use it directly without invoking this skill: ```bash research-hub auto "TOPIC" --with-crystals --llm-cli codex research-hub auto "TOPIC" --with-crystals --llm-cli gemini ``` Pick `codex` for token-heavy mechanical generation; pick `gemini` for long-context reading or CJK output. If you also need a second delegate in the same round (e.g. translate the resulting brief to zh-TW with Gemini), then this becomes a multi-AI plan and the router applies. Check available CLIs: ```bash python -c "from research_hub.auto import detect_llm_cli; print(detect_llm_cli())" ``` ## Guardrails - Do not produce a plan with a single task — that is a misuse; use the leaf skill directly. - Do not fabricate citations or metadata in either the plan or the per-task briefs. - Do not assume Gemini is Chinese-only; route by task character (long context, CJK prose, second-opinion review), not by language alone. - Do not overwrite `.coord/multi_ai_plan.md` of a different plan_id — append a new file `.coord/multi_ai_plan_.md` if the workspace already has an active plan. - Do not overwrite vault notes or delete clusters without explicit user approval. --- > Source: [WenyuChiou/research-hub](https://github.com/WenyuChiou/research-hub) — distributed by [TomeVault](https://tomevault.io).