optimizing-tokens

name	optimizing-tokens
description	AI agent maximizes efficiency and minimizes costs through strategic token usage while maintaining output quality. Use when managing AI interactions, designing prompts, or reducing costs. Use when this capability is needed.
metadata	{"author":"doanchienthangdev"}

Optimizing Tokens

Quick Start

1. Analyze - Identify input vs output token distribution
2. Minimize Context - Read only relevant file sections, not entire files
3. Optimize Prompts - Use direct commands, remove filler words
4. Structure Outputs - Request concise formats (JSON over prose)
5. Batch Operations - Combine related requests, avoid duplicate context
6. Select Model - Match model tier to task complexity

Features

Feature	Description	Guide
Context Targeting	Read only needed code sections	Line ranges, pattern search, summaries
Prompt Efficiency	Direct commands vs verbose requests	79% reduction possible
Output Formatting	Structured concise responses	JSON/YAML over verbose explanations
Model Selection	Right model for task complexity	Haiku: simple, Sonnet: standard, Opus: complex
Batching	Combine related operations	Single request with multiple outputs
Caching	Avoid redundant computation	Cache by content hash + timestamp

Common Patterns

# Prompt Optimization (79% reduction)
INEFFICIENT (120 tokens):
"I would really appreciate it if you could help me
with this task. What I need you to do is to please
analyze this code and look for any bugs..."

EFFICIENT (25 tokens):
"Analyze for bugs, error handling issues, security.
For each: location, problem, fix."

# Context Optimization
INEFFICIENT: Read entire 1000-line file
EFFICIENT: Read lines 45-60 around target function

# Output Format
INEFFICIENT: "Please explain in detail..."
EFFICIENT: "Output: JSON {name, severity, fix}"

# Batching
INEFFICIENT:
  Request 1: "Given code [100 lines], find bugs"
  Request 2: "Given code [same 100 lines], add types"

EFFICIENT:
  Single request: "Given code [100 lines]:
  1. Find bugs
  2. Add types"

# Model Selection Guide
| Task Type | Model | Examples |
|-----------|-------|----------|
| Simple | Haiku | Formatting, syntax check, lookups |
| Standard | Sonnet | Features, bugs, reviews, tests |
| Complex | Opus | Architecture, security, critical code |

# Search Efficiency
INEFFICIENT: grep ".*" / (matches everything)
EFFICIENT: grep "handleAuth" src/ --type ts

Best Practices

Do	Avoid
Read only what's needed - use line ranges	Reading entire files for one function
Use direct language - commands over requests	Verbose, polite phrasing in prompts
Structure outputs - JSON/YAML over prose	Requesting detailed explanations for simple tasks
Batch operations - combine related requests	Repeating context across multiple requests
Choose right model - Haiku for simple tasks	Using most powerful model for everything
Limit search results - use head_limit	Unbounded searches returning thousands of results
Cache results - avoid redundant computation	Re-analyzing unchanged files
Progressive loading - start minimal, expand	Loading full context when partial suffices

Related Skills

• dispatching-parallel-agents - Efficient multi-agent patterns
• writing-plans - Structured planning reduces iteration
• thinking-sequentially - Organized reasoning saves tokens

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