Usage Optimization Skill

Version: 1.0.0
Category: Optimization
Triggers: High usage alerts, efficiency improvements, batch operations

Quick Reference

Effectiveness Ratings

Best Practice: Execution Over Description

❌ BAD: "Can you describe what analyze_data.py does?"
    Result: Long description, no actionable output

✅ GOOD: "Prepare input file for data analysis and provide command"
    Result: Working configuration + executable command + actual results

Optimal Workflow Pattern

1. ⭐⭐⭐⭐⭐ AI prepares input YAML file
   └─ Following template in templates/input_config.yaml
   └─ Validated against schema
   └─ Version controlled in config/input/

2. ⭐⭐⭐⭐⭐ AI provides exact bash command
   └─ Points to correct script in scripts/
   └─ References prepared input file
   └─ Includes all necessary flags

3. ⭐⭐⭐⭐⭐ User executes command
   └─ Copy/paste provided command
   └─ Review output and results
   └─ Version control any changes

4. ⭐⭐⭐⭐⭐ Use Claude for git operations
   └─ Commit results
   └─ Create meaningful commit messages
   └─ Manage branches and PRs

Prompt Optimization

Context-First Prompts

## Task Context
- Repository: digitalmodel (Work)
- Complexity: Medium
- Time sensitivity: Production hotfix
- Dependencies: None
- Testing required: Yes

## Specifications
[Full specifications here]

## Output Format
[Exact format needed]

## Constraints
[Any limitations]

Generate [specific deliverable] following this context.

Batch Operations Template

I need to perform the following operations across multiple repositories:

## Scope
- Repositories: [list or "all work" or "all personal"]
- Operation type: [commit/sync/test/build/deploy]

## Configuration

operation: batchcommit scope: workrepositories config: message: "Update dependencies to latest" autopush: true runtests: true

## Expected Output
- Status report per repository
- Aggregate success/failure metrics
- Next actions if any failures

Anti-Patterns to Avoid

❌ Description-Only Requests

BAD: "Describe what this script does"
Result: No actionable output, wasted tokens

❌ Skipping Questions

BAD: Directly generating from vague requirements
GOOD: "Before generating, I need to understand: [list]"

❌ Making Assumptions

BAD: "I'll assume we want JWT authentication"
GOOD: "Should we use JWT, sessions, or OAuth?"

Usage Monitoring Commands

# Check usage
./scripts/monitoring/check_claude_usage.sh check

# View today's summary
./scripts/monitoring/check_claude_usage.sh today

# View recommendations
./scripts/monitoring/check_claude_usage.sh rec

# Log a task
./scripts/monitoring/check_claude_usage.sh log sonnet digitalmodel "Feature work"

Daily Checklist

Before Starting Work:

• Check usage at https://claude.ai/settings/usage
• Note Sonnet percentage
• Plan model distribution for session
• Batch similar tasks together

During Work:

• Use Haiku for quick queries
• Reserve Sonnet for standard implementations
• Use Opus only for complex decisions
• Batch related questions

End of Session:

• Review usage increase
• Update usage log
• Plan next session if approaching limits

Target Metrics

Full Reference

See: @docs/AIAGENTUSAGEOPTIMIZATIONPLAN.md See: @docs/modules/ai/AIUSAGEGUIDELINES.md

Use this when optimizing AI usage, improving efficiency, or managing usage limits.