Inbox Processing Example

NOTE: This is an example skill showing how to build an inbox processing workflow. The actual inbox-processing skill is gitignored as it contains personal workflow patterns. Copy this to .claude/skills/inbox-processing/ and customize for your needs.

Overview

Process large Things3 inboxes (100+ items) efficiently through batch analysis, confidence-based automation, and intelligent user interaction.

Prerequisites:

• Load things3-productivity skill for MCP tool patterns

• Configure private-prefs/personal-taxonomy.json with your work areas and tags

• Create temp/inbox-processing/ folder for session state

When to use: Inbox has 100+ items requiring organization.

Personal Organization Integration

The skill uses LLM-driven analysis with context from personal-taxonomy.json :

• Work identification: Your configured work tags and areas

• Priority system: Your 1-9 priority scale

• Project patterns: Your existing projects and content patterns

• Semantic matching: Based on meaning, not just keywords

Core Workflow: Batch Processing

Phase 1: Initialize & Analyze

Step 1: Setup Session Create temp/inbox-processing/ with tracking files:

session.md # Batch progress, statistics match_results.json # Decisions with confidence scores pending_decisions.json # Items awaiting approval high_confidence_actions.json # Auto-apply candidates (≥90%) execution_log.md # Complete action history

Step 2: Load Inbox Batch

First batch: 50 items, subsequent: 50-100 items

read_tasks(when="inbox", limit=50, include_notes=True)

Step 3: Load System Inventory Cache once per session:

list_areas() # All areas with IDs and tags list_projects() # All projects with metadata list_tags() # All tags including hierarchy

Phase 2: Confidence-Based Analysis

Step 4: Analyze Each Item For each inbox item, determine:

• Area assignment (90%+ confidence threshold)

• Project assignment (85%+ confidence threshold)

• Tag additions (based on content and context)

• Reference detection (notes without actionable tasks)

Confidence Levels:

• 90-100%: Auto-apply safe (e.g., "Work: Fix bug" → area="Work")

• 80-89%: Present for batch approval

• Below 80%: Skip, handle manually

Phase 3: User Interaction

Step 5: Present High-Confidence Batch Group by action type:

Area: Work (25 items, 90-100% confidence)

Auto-assign these 25 items to area="Work"?

• "Work: Fix login bug" (100%)
• "Dashboard review" (95%) ...

[Approve] [Review individually] [Skip]

Step 6: Handle Medium-Confidence Items Present individually for 80-89% confidence:

1. "Design review notes" (85%) → area="Work"? Notes: Contains work-related keywords [Yes] [No] [Different area]

Phase 4: Execution

Step 7: Execute Approved Actions Batch operations by type:

Set areas

edit_task(task_uuid="...", area="Work")

Add tags

add_tags(task_uuids=[...], tags=["urgent"])

Create projects

create_project(name="Q4 Roadmap", area="Work")

Step 8: Handle Reference Items Items with notes but no actionable task:

Suggest migration to Notion

migrate_inbox_to_notion(block_id="your-block-id")

Phase 5: Completion

Step 9: Update Statistics Track in session.md :

Batch 1: 50 items processed

• 25 auto-assigned to areas
• 10 tagged
• 5 moved to projects
• 10 pending review

Remaining: 96 items

Step 10: Next Batch If inbox > 0, repeat from Step 2 with larger batch size (up to 100).

Pattern Learning

The skill improves through use:

• Successful matches reinforce confidence thresholds

• User corrections inform future suggestions

• Project creation patterns learned from history

• Tag combinations tracked for consistency

Example Confidence Scoring

High Confidence (90-100%)

"Work: Fix dashboard bug" → area="Work"

• Explicit area mention (100%)
• Work tag keyword present
• Matches existing area pattern

Medium Confidence (80-89%)

"Review team notes" → area="Work"?

• Work context implied (85%)
• No explicit area mention
• Could be personal or work

Low Confidence (<80%)

"Call mom" → ???

• No clear work/personal indicators
• No matching patterns
• Requires manual classification

Customization Guide

To create your own inbox processing skill:

Copy this example:

cp -r .claude/skills/inbox-processing.example .claude/skills/inbox-processing

Update references:

• Replace "Work" with your actual work area names

• Add your specific project patterns

• Customize confidence thresholds

Configure personal-taxonomy.json:

{ "things3": { "work_classification": { "work_tag": "YOUR_WORK_TAG", "work_areas": ["Your Work Area"] } } }

Test with small batches:

• Start with 10-20 items

• Adjust confidence thresholds

• Build pattern database

Tips

• Start conservative: Use higher confidence thresholds (95%+) initially

• Batch approvals: Group similar actions for efficiency

• Reference items: Migrate notes to Notion early to reduce inbox clutter

• Project discovery: Use list_projects=True to avoid creating duplicates

• Session breaks: Process in 30-minute focused sessions

Integration with Other Skills

• things3-productivity: Tool usage patterns and query strategies

• notion-workflows: Reference item migration patterns

• productivity-integration: Cross-system automation