Token Budget Advisor

An early assessment tool that detects token-intensive tasks and provides specific chunking strategies to prevent exceeding context window constraints before work begins.

This skill is ideal for users planning complex, multi-document tasks who want to avoid hitting token limits mid-stream and need strategic guidance on task breakdown.

Core Purpose

The Token Budget Advisor helps you:

Detect token-heavy tasks before you start working
Plan chunking strategies tailored to your specific task
Avoid context overruns by working strategically
Maintain momentum through structured task breakdown

Early Warning System

The advisor identifies token-intensive scenarios:

High-Risk Task Indicators

Triggers that signal potential token issues:

Multiple file uploads (3+ documents)
"Comprehensive" analysis requests
10+ tool calls required for completion
Large-scale processing across many items
Deep multi-stage workflows with extensive outputs

Token Estimation Framework

Rough Consumption Guidelines:

Uploaded documents: 1,000–5,000 tokens each
Web fetches: 2,000–8,000 tokens per fetch
Long-form reports: 5,000–15,000 tokens
Tool call overhead: 1,000–3,000 tokens average per call
Code file analysis: 500–3,000 tokens per file

These are estimates for planning purposes.

Warning Thresholds

Budget warnings trigger at different consumption levels:

60-80% - Caution: Monitor token usage
80-90% - Warning: Consider chunking
90-95% - High risk: Chunking recommended
95%+ - Critical: Chunking required

Five Chunking Strategies

1. Sequential Processing

Time-ordered or phase-based analysis:

Process data by time periods (quarterly, monthly)
Handle project phases separately
Work through stages chronologically
Complete one period before moving to next

Best for: Historical data, timeline analysis, phased projects

2. Dimensional Breakdown

Multi-faceted topic separation:

Analyze different aspects independently
Separate concerns (financial, competitive, regulatory)
Focus on one dimension at a time
Synthesize findings across dimensions

Best for: Complex topics with distinct aspects, multi-angle analysis

3. Depth Progression

Iterative refinement cycles:

Cycle 1: Create outline or high-level structure
Cycle 2: Develop draft content
Cycle 3: Refine and polish details
Cycle 4: Final review and completion

Best for: Long-form content, reports, documentation

4. Subset Sampling

Representative analysis across large sets:

Select representative samples
Analyze subset thoroughly
Identify patterns and themes
Generalize findings to full set
Validate with additional samples if needed

Best for: Large document collections, bulk data analysis

5. Parallel Track Processing

Independent workstream separation:

Identify independent components
Process tracks separately
Maintain isolation between tracks
Combine results at the end
Cross-reference for consistency

Best for: Multi-component projects, parallel workflows

Strategic Planning Approach

Prevention Over Recovery:

The advisor intervenes before you start work, not after hitting limits. This prevents:

Lost progress from truncated conversations
Incomplete analysis from mid-task limits
Frustration from unexpected stops
Wasted tokens on aborted attempts

Communication Style

The advisor takes a solution-oriented approach:

Matter-of-fact rather than apologetic
Frames chunking positively as improving thoroughness
Maintains user control over strategy selection
Keeps momentum toward task completion
Actionable recommendations not just warnings

Chunking Benefits

Strategic task breakdown offers advantages beyond token management:

Improved Quality

Deeper focus on each chunk
More thorough analysis per section
Better attention to detail
Reduced cognitive overload

Better Organization

Clear task structure
Logical progression
Easier to track progress
Natural checkpoints

Flexibility

Adjust strategy mid-course if needed
Reprioritize based on findings
Pause and resume easily
Iterate on specific sections

Maintained Context

Keep relevant information available
Avoid truncating important details
Preserve conversation continuity
Complete thoughts and analysis

Practical Recommendations

The advisor provides specific guidance:

Chunk size suggestions based on task complexity
Processing order optimized for dependencies
Checkpoint placement for natural breaks
Synthesis strategies for combining chunks
Fallback plans if initial approach doesn't work

Task Assessment Process

Three-Step Evaluation:

Estimate total token requirements
- Count inputs (files, fetches)
- Estimate processing overhead
- Project output size
Compare against available budget
- Calculate percentage utilization
- Identify warning threshold
- Determine if chunking needed
Recommend specific strategy
- Select appropriate chunking approach
- Provide actionable plan
- Outline execution steps

When the Advisor Activates

The advisor triggers for requests involving:

Analysis of multiple large documents
Comprehensive reports or deliverables
Multi-stage complex workflows
Large-scale data processing
Tasks with "thorough" or "comprehensive" modifiers

Integration with Workflow

The advisor works seamlessly:

Early intervention before starting work
Quick assessment doesn't delay task
Clear recommendations easy to follow
Optional guidance you choose the approach
Maintains momentum toward completion

Repository Resources

The repository includes token estimation tools, chunking strategy templates, budget calculators, and workflow planning guides for efficient task management.

Visit the Token Budget Advisor repository for complete planning tools and strategies.

About This Skill

This skill was created by Nate Jones as part of his comprehensive Nate's Substack Skills collection. Learn more about Nate's work at Nate's Newsletter.

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Early assessment tool for token-heavy tasks providing chunking strategies and budget planning to prevent context window overruns before work begins.