tools-only Token Budget Advisor
This skill provides early assessment of token-heavy tasks and recommends chunking strategies to ensure successful completion within context window constraints.
When to Use This Skill
Trigger this skill before beginning work when you detect:
- Multiple file uploads (3+ documents) combined with analysis requests
- Requests for "comprehensive", "complete", "thorough", or "full" analysis
- Multi-document comparative analysis
- Complex workflows requiring 10+ tool calls (extensive web research + synthesis)
- Tasks combining heavy research with large artifacts (reports, presentations)
- Queries spanning multiple dimensions (temporal + categorical + quantitative)
- Requests to "analyze everything" or "create a complete report on all aspects"
Core Function
This skill serves two purposes:
- Early warning system: Assess whether a task will likely exceed token limits
- Strategic planning: Provide specific, actionable chunking recommendations
Token Estimation Framework
Quick Assessment Heuristics
Estimate token consumption using these rough guidelines:
Input costs:
- Uploaded document: ~1,000-5,000 tokens each (depending on length)
- Web search result: ~500-1,500 tokens
- Web fetch (full article): ~2,000-8,000 tokens
- Google Drive document: ~1,000-10,000 tokens (varies significantly)
Output costs:
- Simple response: 500-2,000 tokens
- Detailed analysis: 2,000-5,000 tokens
- Long-form report: 5,000-15,000 tokens
- Complex artifact (presentation, document): 5,000-20,000 tokens
Tool call overhead:
- Each tool call includes the query, results, and reasoning: ~1,000-3,000 tokens average
Warning thresholds:
- Caution zone (60-80% of budget): Task is achievable but tight; consider efficiency
- Danger zone (80-95% of budget): High risk; strongly recommend chunking
- Exceeds budget (95%+ of budget): Task requires chunking; cannot complete in one conversation
Task Complexity Multipliers
Apply these mental adjustments:
- Synthesis required: Add 30-50% to output estimate (comparing, integrating multiple sources)
- Iterative refinement: Add 20-30% (when task involves reviewing and improving)
- Multiple formats: Add 20% per additional output type (report + presentation + spreadsheet)
Chunking Strategy Framework
When a task exceeds token budget, recommend specific chunking approaches. Choose strategies based on task structure:
1. Sequential Processing
Best for: Time-series data, chronological analysis, ordered workflows
Pattern:
"This analysis of 12 months of data will exceed our token budget. I recommend we split it into quarters:
- Part 1: Q1-Q2 analysis (Jan-Jun)
- Part 2: Q3-Q4 analysis (Jul-Dec)
- Part 3: Synthesis and recommendations
Should I start with Part 1?"
When to use:
- Historical data analysis
- Period-over-period comparisons
- Multi-phase projects
2. Dimensional Breakdown
Best for: Multi-faceted analysis, different aspects of same topic
Pattern:
"A complete market analysis covering financial, competitive, regulatory, and technological factors will strain our token budget. Let's break it into:
- Session 1: Financial performance and market size
- Session 2: Competitive landscape and positioning
- Session 3: Regulatory environment and compliance
- Session 4: Technology trends and synthesis
Which dimension should we tackle first?"
When to use:
- Multi-stakeholder analysis
- Different analytical lenses on same subject
- Complex business cases
3. Depth Progression
Best for: Tasks requiring outline → draft → refinement
Pattern:
"Creating a comprehensive 50-slide presentation with detailed research will exceed our budget. I recommend:
- Round 1: Build structure and outline (30 min)
- Round 2: Develop content for slides 1-25 (45 min)
- Round 3: Develop content for slides 26-50 (45 min)
- Round 4: Refinement pass (30 min)
Let's start with the outline?"
When to use:
- Large documents or presentations
- When quality refinement is important
- Creative projects benefiting from iteration
4. Subset Sampling
Best for: Large document sets where representative sampling works
Pattern:
"Analyzing all 15 contracts will exceed our budget. I suggest:
- Part 1: Analyze 5 representative contracts (different types/dates)
- Part 2: Based on patterns found, confirm with 5 more
- Part 3: Quick scan of remaining 5 for exceptions, then synthesize
This gives thorough coverage while managing tokens. Sound good?"
When to use:
- Document review at scale
- Pattern identification across many files
- Risk-based sampling approaches
5. Parallel Track Processing
Best for: Independent workstreams that can be combined later
Pattern:
"Comparing our product vs 5 competitors across features, pricing, and positioning is too large for one session. Let's split by competitor:
- Session 1: Competitors A & B full analysis
- Session 2: Competitors C & D full analysis
- Session 3: Competitor E + synthesis matrix
Each session stays focused and manageable."
When to use:
- Comparative analysis
- Multiple independent subjects
- When parts don't need each other's context
Communication Guidelines
Messaging Framework
When recommending chunking, use this structure:
- Acknowledge the request clearly
- Provide token budget assessment (brief, 1 sentence)
- Recommend specific chunking approach (numbered list, 2-4 parts)
- Ask for confirmation to proceed (keep user in control)
Example:
I'll help you analyze these 8 financial reports and create a comprehensive presentation.
This task will exceed our token budget given the research and artifact creation required.
I recommend splitting it into:
1. Reports 1-4: Analysis and key findings
2. Reports 5-8: Analysis and key findings
3. Synthesize all findings into presentation
Should I start with reports 1-4?
What NOT to Do
❌ Don't over-explain token budgets or get technical about context windows ❌ Don't apologize excessively or sound limiting ❌ Don't provide vague suggestions like "maybe split this up somehow" ❌ Don't start work and then stop mid-task saying "we've run out of tokens"
✅ Do be matter-of-fact and solution-oriented ✅ Do provide specific, actionable breakdowns ✅ Do keep the momentum going toward task completion ✅ Do frame chunking as a quality improvement (thoroughness) not limitation
Handling Edge Cases
User Insists on Single Session
If user pushes back on chunking:
"I understand you'd prefer this in one go. I'll do my best to complete it, but I may need to:
- Prioritize the most critical elements
- Provide a condensed version
- Focus on breadth over depth in some areas
Let me start and we'll see how far we can get. What aspects are highest priority?"
Task Becomes Too Large Mid-Stream
If partway through, token budget becomes concerning:
"I'm about halfway through and we're approaching token limits. I have two options:
1. Complete this current section and continue in a fresh conversation (recommended - maintains quality)
2. Accelerate through remaining sections with lighter analysis
Which approach works better for you?"
Uncertain Estimation
When task scope is ambiguous:
"I want to make sure we complete this successfully. The scope could go in different directions. Could you clarify:
- [Specific question about depth]
- [Specific question about breadth]
This helps me gauge whether we should chunk this task."
Integration with Other Skills
This skill works in conjunction with domain-specific skills:
- Before heavy document analysis: Check token budget, then use docx/pdf/xlsx skills
- Before comprehensive research: Assess scope, then execute research process
- Before complex artifacts: Plan chunking, then use pptx/docx/xlsx creation skills
Think of this skill as a "pre-flight check" before embarking on token-intensive tasks.
Examples in Action
Example 1: Multi-Document Analysis
User query: "Analyze all these uploaded contracts and tell me the common terms and differences" [User has uploaded 12 PDF contracts]
Response: "I'll help you analyze these 12 contracts. Given the volume, I recommend we process this in batches to ensure thorough analysis:
- Contracts 1-4: Extract key terms, obligations, and unique clauses
- Contracts 5-8: Same analysis
- Contracts 9-12: Same analysis
- Synthesis: Common terms across all + key differences
This ensures I can give each contract proper attention. Should I start with contracts 1-4?"
Example 2: Comprehensive Research Report
User query: "Research the AI chip market and create a detailed report covering market size, key players, technology trends, and 5-year forecast"
Response: "I'll create a comprehensive AI chip market report. This research and report creation will be substantial, so I recommend:
- Market overview: Size, growth, segments (research + draft)
- Competitive landscape: Key players, market share, strategies (research + draft)
- Technology trends: Current developments, emerging tech (research + draft)
- Future outlook: 5-year forecast, implications (research + draft)
- Final report assembly: Executive summary, polish, formatting
Each section gets thorough research and quality writing. Should I begin with the market overview?"
Example 3: Simple Task (No Chunking)
User query: "Summarize this 10-page PDF and give me the key takeaways"
Response: [No trigger - proceed normally without invoking this skill] "I'll read through the PDF and extract the key points for you."
Rationale: Single document summary is well within normal token budget.
Skill Maintenance
This skill should be updated when:
- Token budget limits change
- New patterns of token-heavy tasks emerge
- Chunking strategies prove ineffective in practice
- User feedback indicates communication could be clearer