Prompt Token Analyzer for Openclaw

A lightweight Node.js CLI tool for analyzing prompt token counts and estimating LLM costs using GPT-compatible tokenization.

putixiaosheng
v1.0.1
Mar 13, 2026
0
888
0

Install & Download

1. ClawHub CLI

The fastest way to install a skill directly from the registry.

npx clawhub@latest install prompt-token-analyzer

2. Manual Installation

Copy the skill folder to one of these locations

Global
~/.openclaw/skills/
Workspace
<project>/skills/

Priority: Workspace > Local > Bundled

3. Prompt Installation

Copy this prompt to OpenClaw to install it automatically.

Help me install prompt-token-analyzer using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).

Prefer to download?

Get the raw skill files in a ZIP archive.

What is Prompt Token Analyzer?

The Prompt Token Analyzer is a technical utility designed to provide developers with precise control over their language model interactions. By leveraging the gpt-tokenizer library, it allows users of Openclaw Skills to accurately simulate how a prompt will be broken down by OpenAI-style models before making an API call. This tool is essential for maintaining cost-efficiency and ensuring that complex prompts or retrieved data fit within specific context window constraints.

As a foundational component for those building with Openclaw Skills, this analyzer provides immediate feedback on character counts, token counts, and the density of information within your text. Whether you are building autonomous agents or complex RAG pipelines, having a local method to verify tokenization saves time and prevents avoidable API errors caused by context overflow.

Prompt Token Analyzer Use Cases

  • Prompt Engineering: Quantify how adjustments to system instructions or few-shot examples impact the total token footprint within Openclaw Skills.
  • RAG Context Analysis: Verify the size of retrieved document chunks to ensure they don't exceed model limits during the augmentation phase.
  • Debugging Context Overflow: Rapidly identify which parts of a large prompt are consuming the most tokens to facilitate effective pruning.
  • Cost Estimation: Calculate the projected financial impact of high-volume LLM tasks before execution.

How Prompt Token Analyzer Works

  1. The user provides input to the tool via either a file path using the analyze command or a raw string using the text command.
  2. The utility invokes the gpt-tokenizer library to process the input through a GPT-compatible encoding scheme.
  3. It calculates metrics including total character count, final token count, and the average number of characters per token.
  4. The tool applies a cost-per-million-tokens calculation to provide a financial estimate for the processed prompt.
  5. Results are printed to the console in a clean, readable format for immediate evaluation by the developer using Openclaw Skills.

Prompt Token Analyzer Setup

To get started with this tool from the Openclaw Skills collection, first install the necessary tokenizer dependency:

npm install -g gpt-tokenizer

Next, create the executable script by running the following command in your terminal:

cat <<'EOF' > prompt-token
#!/usr/bin/env node

import { encode } from "gpt-tokenizer"
import fs from "fs"

const args = process.argv.slice(2)

if (args.length === 0) {
  console.log("Usage:")
  console.log("  prompt-token analyze <file>")
  console.log("  prompt-token text \"your prompt here\"")
  process.exit(1)
}

let text = ""

if (args[0] === "analyze") {
  const file = args[1]
  if (!file) {
    console.error("Missing file path")
    process.exit(1)
  }
  text = fs.readFileSync(file, "utf8")
} else if (args[0] === "text") {
  text = args.slice(1).join(" ")
} else {
  console.error("Unknown command")
  process.exit(1)
}

const tokens = encode(text)

console.log("Prompt Token Analysis")
console.log("---------------------")
console.log("Characters:", text.length)
console.log("Tokens:", tokens.length)
console.log("Average chars/token:", (text.length / tokens.length).toFixed(2))

const estimatedCost = tokens.length / 1000000 * 5

console.log("")
console.log("Estimated cost (example $5 / 1M tokens):")
console.log("$" + estimatedCost.toFixed(6))
EOF

Finally, make the script executable and move it to your system PATH:

chmod +x prompt-token
sudo mv prompt-token /usr/local/bin/

Prompt Token Analyzer Data Schema & Taxonomy

The Prompt Token Analyzer processes text input and generates a structured statistical report. It handles data according to the following schema:

Attribute Type Description
Input Source File or String The raw text to be tokenized.
Characters Integer The total UTF-8 character count of the input text.
Tokens Integer The count of tokens after GPT-style encoding.
Average Ratio Float The efficiency metric (Characters divided by Tokens).
Estimated Cost Float The financial projection based on a $5/1M token rate.

Prompt Token Analyzer Advanced Features

  • Local Tokenization: Perform token counts offline without sending data to third-party APIs, keeping your Openclaw Skills workflows secure.
  • Multi-Source Input: Support for both direct CLI string arguments and file-based analysis for large datasets.
  • Cost Simulation: Customizable cost logic within the script to match specific LLM provider pricing tiers.
  • Workflow Integration: Designed as a CLI tool that can be easily piped into other Openclaw Skills for automated context management.

SKILL.md


Loading

Related Openclaw Skills

METADATA

Github Stars: 0
forks: 0

Featured*