mundi-orch-multi-llm-route

name	mundi-orch-multi-llm-route
description	Task-type → best-LLM-per-task router. Classifies incoming task (code, long-context research, creative, math, vision, agentic) then dispatches to the right provider (Claude for code, Gemini for long-context, GPT for creative, etc.) per published benchmark + cost profile. Use when composing an orchestrator that needs to call the "right" LLM automatically — or when budget optimization matters across many calls.
allowed-tools	Read, Write, Edit, Bash, Task

Mundi Orch — Multi-LLM Router

Overview

Different LLMs have different strengths. Claude is best at code, reasoning, and tool use. Gemini is strongest on long-context (1M+), vision, and research breadth. GPT is competitive on creative, some math, and has Codex for pure coding. This router classifies a task and dispatches to the best provider per benchmark + cost.

This is the automated version of what you'd do manually when you think "this is a code problem → Claude" or "this is a 500-page document → Gemini."

When to use

• Inside an orchestrator that makes many LLM calls and wants per-call optimization
• When budget matters across a run (expensive tasks → cheap provider when appropriate)
• Building a "best default" for an agentic system that might tackle varied tasks
• Reducing provider-lock-in

Do NOT use when:

• One-off manual call — just pick the LLM yourself
• Task is clearly homogeneous (all code → Claude; all long docs → Gemini) — skip the router overhead
• Cost doesn't matter (single-user, small volume) — default to Claude

Classification taxonomy

task class	signals	best provider	rationale
code-generation	programming language mentioned, code blocks expected, debugging	Claude Sonnet/Opus	SWE-bench leader, tool-use strength
code-review	"review this diff", explicit file review	Claude Opus	deep reasoning, catches edge cases
long-context-research	>50k tokens of input, multi-doc synthesis	Gemini 3.1 Pro (1M context)	only model that fits without sharding
vision-extraction	images, PDFs, screenshots, layout parsing	Gemini 3.1 Pro	strongest vision + cheap
creative-writing	blog, marketing copy, brand voice	GPT-4 / Claude	GPT more playful, Claude more structured
math-heavy	numerical computation, derivations	GPT-o1 / Claude Opus + tools	o1 good at pure, Claude good with calculator tool
agentic-decomposition	break-this-into-sub-tasks, multi-step	Claude Opus	best tool-use + plan-decompose
summarization-short	<10k input, TL;DR output	Claude Haiku / Gemini Flash	cheap, fast, good enough
structured-extraction	"extract JSON from this"	Claude Sonnet	reliable JSON mode, fast

Pipeline (3 steps)

[1] Classify task  → regex + light LLM classifier → task class
[2] Pick provider  → lookup from table + current-cost check + rate-limit check
[3] Dispatch       → call via provider SDK; return result with metadata tag

I/O contract (MWP)

state_reads:

• ~/Mundi Princeps/config/api_keys.json — all provider keys
• ~/.claude/skills/saraev-cc-opus-vs-sonnet-routing/SKILL.md — Claude-internal routing pattern (reused here)
• ~/.claude/skills/saraev-cc-conductor-multimodel/SKILL.md — multi-model conductor pattern

state_writes:

• Optional apps/router-log/<date>.jsonl — decision log per routed call (for audit + cost accounting)

Composition

component	tool
classifier	Claude Haiku with 3-shot prompt, returns task class + confidence
Claude dispatch	claude-agent-sdk or subprocess
Gemini dispatch	curl pattern from video-to-action/scripts/analyze-youtube.sh
GPT dispatch	saraev-cc-codex-diversify OR OpenAI API
rate-limit tracker	simple file-lock counter per provider in /tmp/mundi-llm-rate-*.json
cost calculator	token count × provider price-per-token (update quarterly)

Routing rules

Default preference:

1. Cheapest acceptable — if task is simple and Haiku/Flash suffice, use them.
2. Right-fit over cost — if long-context is needed, don't shard to save; use Gemini directly.
3. Fallback cascade — provider down → next-best per class.
4. Sticky per-run — if a run involves many calls with the same task class, don't re-classify; pin to one provider.

# Pseudocode
class_, confidence = classify(task)
provider = PROVIDER_TABLE[class_]
if not provider_available(provider):
    provider = FALLBACK_TABLE[class_][0]
if budget_exceeded(provider):
    provider = cheaper_alternative(class_)
return dispatch(provider, task)

Failure modes

failure	recovery
Classifier low-confidence	default to Claude Opus (safe) and log for review
Primary provider down	cascade to next in FALLBACK_TABLE for that class
Rate-limit hit	wait 30s + retry, or route to alternative
Budget exceeded (soft limit)	surface warning + route to cheaper alternative; don't hard-block
All providers down	hard-fail; do not synth a response

Invocation

Skill(skill="mundi-orch-multi-llm-route", {
  task: "Summarize this 400-page data room into a 2-page IC brief",
  hint_class: "long-context-research",  # optional override
  budget_ceiling_usd: 2.00,
  log_decision: true
})

# Returns:
{
  "classified_as": "long-context-research",
  "provider_used": "gemini-3-pro",
  "fallback_chain": ["gemini-3-pro", "claude-opus-4.7-1m"],
  "response": "...",
  "cost_usd": 0.47,
  "latency_ms": 18400
}

Cross-references

• Related: saraev-cc-opus-vs-sonnet-routing (Claude-internal), saraev-cc-conductor-multimodel, saraev-cc-claude-code-token-cost-optimization, mundi-orch-multi-llm-consensus, mundi-orch-multi-llm-debate, router-hub (skill/tool discovery, different layer)
• Plugin skills: claude-agent-sdk, claude-api
• Memory: (none specific; patterns from saraev-cc-* family)
• KB: docs/knowledge-base/wiki/01-ai-development-and-agents/1.3-llm-infrastructure.md, wiki/02-workflow-and-dx/token-optimization.md
• Plan source: docs/plans/2026-04-19-phase-3-final.md line 864

Safety

• Keep classifier cheap. Use Haiku/Flash for classification — expensive classifier defeats the purpose.
• Log every decision — retrospectively tune the routing table against actual outcomes.
• Don't shard when not needed. If Gemini can fit it in 1M context, don't chunk to save a few cents.
• Provider diversity also matters — avoid 100% routing to one provider even if cheapest; keeps you hedged against provider outages.