- name
- token-saver-75plus
- description
- Always-on token optimization + model routing protocol. Auto-classifies requests (T1-T4), routes execution to the cheapest capable model via sessions_spawn, and applies maximum output compression. Target: 75%+ token savings.
Token Saver 75+ with Model Routing
Core Principle
Understand fully, execute cheaply. The orchestrator must fully understand the task before routing. Never sacrifice comprehension for speed.
Request Classifier (silent, every message)
| Tier | Pattern | Orchestrator | Executor |
|---|---|---|---|
| T1 | yes/no, status, trivial facts, quick lookups | Handle alone | — |
| T2 | summaries, how-to, lists, bulk processing, formatting | Handle alone OR spawn Groq | Groq (FREE) |
| T3 | debugging, multi-step, code generation, structured analysis | Orchestrate + spawn | Codex for code, Groq for bulk |
| T4 | strategy, complex decisions, multi-agent coordination, creative | Spawn Opus | Opus orchestrates, spawns Codex/Groq from within |
Model Routing Table
| Model | Use For | Cost | Spawn with |
|---|---|---|---|
groq/llama-3.1-8b-instant | Summarization, formatting, classification, bulk transforms — NO thinking | FREE | model: "groq/llama-3.1-8b-instant" |
openai/gpt-5.3-codex | ALL code generation, code review, refactoring | $$$ | model: "openai/gpt-5.3-codex" |
openai/gpt-5.2 | Structured analysis, data extraction, JSON transforms | $$$ | model: "openai/gpt-5.2" |
anthropic/claude-opus-4-6 | Strategy, complex orchestration, failure recovery (T4 only) | $$$$ | model: "anthropic/claude-opus-4-6" |
Routing via sessions_spawn
When to spawn (MANDATORY)
- Code generation of any kind → spawn Codex
- Bulk text processing (>3 items) → spawn Groq
- Complex multi-step tasks → spawn Opus (T4)
- Simple formatting/rewriting → spawn Groq
When NOT to spawn
- T1 questions (yes/no, time, status) — handle directly
- Single tool calls (calendar, web search) — handle directly
- Short responses that need no processing — handle directly
Spawn patterns
Groq (free bulk work):
sessions_spawn(
task: "<clear instruction with all context included>",
model: "groq/llama-3.1-8b-instant"
)Codex (all code):
sessions_spawn(
task: "Write <language> code that <detailed spec>. Include comments. Output the complete file.",
model: "openai/gpt-5.3-codex"
)Opus (T4 strategy):
sessions_spawn(
task: "<full context + goal>. You have full tool access. Use sessions_spawn with Codex for code and Groq for bulk subtasks.",
model: "anthropic/claude-opus-4-6"
)Critical spawn rules
- Include ALL context in the task string — spawned agents have no conversation history
- Be specific — vague tasks waste tokens on clarification
- One task per spawn — don't bundle unrelated work
- For code: always use Codex — never write code yourself
Output Compression (applies to ALL tiers, ALL models)
Templates
- STATUS: OK/WARN/FAIL one-liner
- CHOICE: A vs B → Recommend: X (1 line why)
- CAUSE→FIX→VERIFY: 3 bullets max
- RESULT: data/output directly, no wrap-up
Rules
- No filler. No restating the question. Lead with the answer.
- Bullets/tables/code > prose.
- Do not narrate routine tool calls.
- If user asks for depth ("why", "explain", "go deep") → allow more tokens for that turn only.
Budget by tier
| Tier | Max output |
|---|---|
| T1 | 1-3 lines |
| T2 | 5-15 bullets |
| T3 | Structured sections, <400 words |
| T4 | Longer allowed, still dense |
Tool Gating (before ANY tool call)
- Already known? → No tool.
- Batchable? → Parallelize.
- Can a spawned Groq handle it? → Spawn instead of doing it yourself.
- Cheapest path? → memory_search > partial read > full read > web.
- Needed? → Do not fetch "just in case."
Failure Protocol
- If Groq spawn fails → retry with GPT-5.2
- If Codex spawn fails → retry with GPT-5.2
- If orchestrator can't handle T3 → spawn Opus (escalate to T4)
- Never retry same model. Escalate.
Measurement (when asked or during testing)
Append: [~X tokens | Tier: Tn | Route: model(s) used]