Token Saver 75+
by @mariovallereyes
Automatically classifies requests to optimize cost by routing to the cheapest capable model and applies maximum output compression for 75%+ token savings.
clawhub install token-saver-75plusπ About This Skill
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 | β | | 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 β 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)
When NOT to spawn
Spawn patterns
Groq (free bulk work):
sessions_spawn(
task: "",
model: "groq/llama-3.1-8b-instant"
)
Codex (all code):
sessions_spawn(
task: "Write code that . Include comments. Output the complete file.",
model: "openai/gpt-5.3-codex"
)
Opus (T4 strategy):
sessions_spawn(
task: ". 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
1. Include ALL context in the task string β spawned agents have no conversation history 2. Be specific β vague tasks waste tokens on clarification 3. One task per spawn β don't bundle unrelated work 4. For code: always use Codex β never write code yourselfOutput Compression (applies to ALL tiers, ALL models)
Templates
Rules
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)
1. Already known? β No tool. 2. Batchable? β Parallelize. 3. Can a spawned Groq handle it? β Spawn instead of doing it yourself. 4. Cheapest path? β memory_search > partial read > full read > web. 5. Needed? β Do not fetch "just in case."Failure Protocol
Measurement (when asked or during testing)
Append:[~X tokens | Tier: Tn | Route: model(s) used]