Overview
- Skill Key
- flynndavid/context-budget-optimizer
- Author
- flynndavid
- Source Repo
- openclaw/skills
- Version
- 1.0.0
- Source Path
- skills/flynndavid/context-budget-optimizer
- Latest Commit SHA
- 9b976dbeda7f8e5e6b71ac03ec47435e120cba9e
Stars
0
Installs
0
Status
ACTIVE
Visibility
PUBLIC
直接复制以下提示词,发送给你的 AI 助手即可完成安装。
请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 context-budget-optimizer 技能。 若已安装,则直接安装 context-budget-optimizer 技能。
# Context Budget Optimizer
**Framework: The Token Efficiency Matrix**
*Worth $200/hr consultant time. Yours for $19.*
---
## What This Skill Does
Audits your agent's token usage across every context layer, identifies where you're burning budget on bloat, and produces a 3-week cost reduction roadmap with concrete implementation steps.
**Problem it solves:** Power users hitting $200-500/month in AI costs often have 60-70% waste baked into their context. Most of it is invisible: stale files in system prompts, redundant skill loading, oversized memory files, wrong model choices. The Token Efficiency Matrix makes the waste visible and rankable.
---
## The Token Efficiency Matrix
A 4-quadrant audit tool that scores every context element by **cost** (token weight) and **ROI** (value delivered per token). High cost + low ROI = cut first.
### The Matrix
```
HIGH ROI
│
KEEP │ OPTIMIZE
(High ROI, │ (High ROI,
Low Cost) │ High Cost)
│
LOW COST ──────────────┼────────────────── HIGH COST
│
AUDIT │ CUT
(Low ROI, │ (Low ROI,
Low Cost) │ High Cost)
│
LOW ROI
```
**Action by quadrant:**
- **KEEP:** Don't touch. It's working efficiently.
- **OPTIMIZE:** Compress or lazy-load. Value is there, just expensive.
- **AUDIT:** Review quarterly. Low cost so not urgent, but ROI should be questioned.
- **CUT:** Kill immediately. You're paying for nothing.
---
## Phase 1: Context Inventory
**Before scoring, map everything that's in your agent's context.**
### Context Layers to Audit
```
Layer A: System Prompt / SOUL.md / Identity files
Layer B: Active skills (loaded per session)
Layer C: Memory files (MEMORY.md, daily notes)
Layer D: Project files injected at startup
Layer E: Tool outputs / MCP responses in context
Layer F: Chat history (conver...
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