skills.rest
luongldptit
luongldptitCOMMUNITY
Explore all skills by this author →
GitHub

token-budget-advisor

Estimate input tokens and select response depth before generation.

Updated Mar 26, 2026
Search Tags:#token-optimization#token-saving#token-budget#ai-response#response-depth#output-control#prompt-efficiency
One-click install
npx skills add https://github.com/luongldptit/move-ticket --skill token-budget-advisor-luongldptit
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: token-budget-advisor
Source: https://github.com/luongldptit/move-ticket/tree/main/.agent/skills/token-budget-advisor
Command: npx skills add https://github.com/luongldptit/move-ticket --skill token-budget-advisor-luongldptit

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill solves the common pain point of unregulated AI response length, where answers are either overly verbose and waste valuable tokens or too brief and lack necessary context, leaving users with no way to control output size before generation.

Core Features & Use Cases

  • Pre-response depth selection: Intercepts the response flow to let users choose their desired answer depth before the AI generates any output.
  • Heuristic token estimation: Calculates approximate input token count and potential response size based on prompt complexity to set accurate expectations for output length.
  • Use case: A user working on a tight token budget can select 25% depth for a quick fact check, while a user needing a full technical analysis can select 100% depth for an exhaustive answer.

Quick Start

Use the token-budget-advisor skill to request a 50% depth response to your question about cloud infrastructure cost optimization.

Frequently Asked Questions about token-budget-advisor

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I control AI response depth and limit token usage?▼

To control AI response depth and limit token usage, you can use heuristic token estimation to calculate prompt complexity, allowing you to select a specific output length tier before generation. This eliminates wasted tokens and prevents insufficient detail.

What is the best way to prevent excessive token waste during prompt generation?▼

The best way to prevent excessive token waste is to intercept the response flow and apply a tiered depth selection mechanism based on heuristic input token estimation. This ensures the AI generates answers matching your exact specified output length.

Can I set a specific token budget for AI technical deep dives and fact-checking?▼

Yes, you can set a specific token budget for technical deep dives and fact-checking by using complexity-based response window calculation. This lets you choose exact depth percentages, such as 25% for quick fact checks or 100% for exhaustive technical analysis.

How does heuristic token estimation work for AI output length control?▼

Heuristic token estimation for output length control works by calculating approximate input token counts and potential response sizes based on prompt complexity. It sets accurate expectations for output length before the AI generates any text.

Do I need manual prompt engineering to achieve a specific AI response brevity?▼

No, you do not need manual prompt engineering to achieve specific AI response brevity. Tiered depth selection automatically delivers user-specified output length by applying complexity-based response window calculation directly to your interaction.

Related Skills

Explore More Software Engineering Skills→
kk20300113-pngkk20300113-png

token-budget-advisor

Estimate input tokens and set tiered response depth levels for AI outputs.

Community
Intermediate
thangvawnthangvawn

token-budget-advisor

Estimate token counts and control AI response depth.

Community
Intermediate
gganbukim1gganbukim1

token-budget-advisor

Estimate prompt size and map complexity to selectable output-length tiers.

Community
Basic
starrank-softstarrank-soft

token-budget-advisor

Intercept AI response generation to offer selectable depth levels based on estimated token consumption.

Official
Intermediate