:PROPERTIES:
:ID:       540c3143-3ca3-4882-abe8-a452b451a8b0
:CREATED:  [2026-04-07 Tue 12:57]
:EDITED:   [2026-04-07 Tue 13:42]
:END:
#+TITLE: PROJECT: Token Optimization (Universal Literate Note)
#+STARTUP: content
#+FILETAGS: :strategy:token:optimization:cost:psf:

* Overview
The *Token Optimization* project defines the strategy and implementation for cost-effective LLM usage. It implements a multi-tier, multi-provider approach to minimize inference costs while maximizing reasoning capability through smart routing and context compression.

* Phase A: Demand (PRD)
:PROPERTIES:
:STATUS: FROZEN
:END:

** 1. Purpose
Minimize LLM operational expenses while maintaining high-fidelity agentic performance.

** 2. User Needs
- *Multi-Tier Strategy:* Resolve tasks using the cheapest model that meets the required intelligence threshold.
- *Failover Resilience:* Automated fallback chain (Gemini -> OpenRouter -> GPT-4o).
- *Context Efficiency:* Implement pruning and RAG to avoid token bloat.
- *Usage Transparency:* Real-time tracking and budget alerts.

** 3. Success Criteria
*** TODO 80% of queries handled by Tier 1 (Free/Fast) models
*** TODO Automated fallback triggered on rate limits
*** TODO Context compression reducing average prompt size by 30%
*** TODO Budget alerts active at 80% threshold

* Phase B: Blueprint (PROTOCOL)
:PROPERTIES:
:STATUS: SIGNED
:END:

** 1. Architectural Intent
Interfaces for dynamic model selection and cost-aware request routing. Source of truth is the `openclaw.json` configuration and real-time provider telemetry.

** 2. Semantic Interfaces
#+begin_src lisp
(defun token-resolve-model (task-complexity)
  "Selects the optimal model tier based on task metadata.")

(defun token-compress-context (raw-context)
  "Applies pruning heuristics to reduce token count.")
#+end_src

* Phase D: Build (Implementation)
Implementation consists of configuration and routing logic located in `projects/token-optimization/`.

** Routing Logic
#+begin_src lisp
;; Logic for complexity-based routing stubs
#+end_src

* Phase E: Chaos (Verification)
Verification involves A/B testing model choices and simulating rate limits to verify fallback integrity.
