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zero-rules

Intercept deterministic tasks (math, time, currency, files, scheduling) BEFORE they hit the LLM. Saves 50-70% on token costs by resolving simple queries locally with zero API calls.

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Status

ACTIVE

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PUBLIC

安装方式

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 zero-rules 技能。 若已安装,则直接安装 zero-rules 技能。

Overview

Skill Key
deeqyaqub1-cmd/zero-rules
Author
deeqyaqub1-cmd
Source Repo
openclaw/skills
Version
-
Source Path
skills/deeqyaqub1-cmd/zero-rules
Latest Commit SHA
15698d122319c80174678975cf3ba1cb99fa126c

Extracted Content

SKILL.md excerpt

# ZeroRules — Deterministic Task Interceptor

## What this skill does

ZeroRules eliminates wasted LLM tokens on tasks that **don't need AI at all**.
Before you send a query to the model, check if ZeroRules can handle it instantly
with zero tokens. Math, time zones, currency conversion, file listing, and
date/scheduling queries all have deterministic answers that cost $0.

**This is not model routing.** Model routing sends simple queries to cheaper models.
ZeroRules skips the model entirely.

## When to use ZeroRules

ALWAYS attempt ZeroRules first when the user's message matches ANY of these patterns:

1. **Math/calculations**: Any arithmetic, percentages, unit conversions
2. **Time queries**: "What time is it in [city]?", "Current time in [timezone]"
3. **Currency conversion**: "$X to EUR", "convert [amount] [from] to [to]"
4. **File operations**: "List files in [dir]", "What's in [folder]?"
5. **Date/scheduling**: "What day is [date]?", "Days until [event]", "Add meeting [details]"

## How to use

Run the ZeroRules engine script at `{baseDir}/rules.js` using Node.js via the
exec tool. Pass the user's message as a single argument:

```bash
node {baseDir}/rules.js "<user message>"
```

### Interpreting the output

The script returns JSON:

- **Rule matched** → `{"matched": true, "rule": "math", "result": "4446", "saved_tokens_est": 850, "session_total_saved": 12.47}`
  Use the `result` value as your response. Do NOT call the LLM for this query.
  Include the savings badge: `🔥 ZeroRules | <rule> | ~<saved_tokens_est> tokens saved | Session: $<session_total_saved> saved`

- **No match** → `{"matched": false}`
  Proceed normally with the LLM. ZeroRules doesn't interfere.

### Examples

User: "What's 247 × 18?"
→ Run: `node {baseDir}/rules.js "What's 247 × 18?"`
→ Output: `{"matched":true,"rule":"math","result":"4,446","saved_tokens_est":850,"session_total_saved":0.02}`
→ Reply: **4,446** 🔥 ZeroRules | math | ~850 tokens saved

User: "What time is it in Tokyo?"
→ Run...

README excerpt

# 🔥 ZeroRules — Stop the API Wallet Assassin

**Intercept deterministic tasks before they burn tokens. Math, time, currency, files, dates → $0.**

Every time your OpenClaw uses Claude Opus to calculate `247 × 18`, you pay ~$0.01 for something a calculator does in 0ms. ZeroRules catches these queries and resolves them locally. Zero tokens. Zero latency.

## The Problem

OpenClaw sends *everything* to your LLM — including tasks that don't need AI:

| Query | Without ZeroRules | With ZeroRules |
|-------|-------------------|----------------|
| "247 × 18" | ~850 tokens, ~$0.01 | **0 tokens, $0** |
| "Time in Tokyo" | ~1,200 tokens, ~$0.01 | **0 tokens, $0** |
| "$100 to EUR" | ~1,500 tokens, ~$0.01 | **0 tokens, $0** |
| "List ~/projects" | ~900 tokens, ~$0.01 | **0 tokens, $0** |
| "Days until Christmas" | ~1,000 tokens, ~$0.01 | **0 tokens, $0** |

These add up. 50 deterministic queries/day × 30 days = **1,500 intercepted calls/month = ~$12-18 saved** just from the built-in rules.

## Install (30 seconds)

### Option 1: ClawHub (recommended)

```bash
clawhub install zero-rules
```

### Option 2: Manual

```bash
cd ~/clawd/skills   # or ~/.openclaw/skills
git clone https://github.com/deeqyaqub1-cmd/zero-rules-openclaw zero-rules
```

### Option 3: Copy-paste

Create `~/clawd/skills/zero-rules/` and copy `SKILL.md` + `rules.js` into it. That's it.

**No dependencies. No API keys. No config. Just Node.js (which OpenClaw already requires).**

## How It Works

1. You ask OpenClaw: *"What's 247 × 18?"*
2. OpenClaw sees ZeroRules is active → runs `rules.js` with your query
3. `rules.js` matches the math pattern → computes `4,446` in 2ms
4. OpenClaw returns the result **without calling the LLM**
5. You see: **4,446** 🔥 ZeroRules | math | ~850 tokens saved

If ZeroRules can't handle it (e.g., *"Write a proposal for Sarah"*), it returns `matched: false` and OpenClaw proceeds with the LLM normally. Zero interference.

## 5 Bui...

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