auto-summary - SKILL.md Agent Skill

name: auto-summary context: fork skill: auto-summary model: haiku description: Batch populate summary fields using content analysis tags: [activity/governance, domain/tooling, automation]

/auto-summary

Batch populate the summary frontmatter field on notes where it is null or missing. The summary field is the highest-value AI triage field — it enables fast note discovery without reading full content.

Usage

/auto-summary                    # Process all notes with null summary
/auto-summary <path>             # Process specific file or folder
/auto-summary --dry-run          # Preview summaries without applying
/auto-summary --type Concept     # Only process specific note type
/auto-summary --limit 50         # Process at most 50 notes

Instructions

Phase 1: Find Notes Needing Summary

Use Grep to find notes with null or missing summary:

# Find notes with summary: null
Grep for "summary: null" in *.md files

# Also find notes with no summary field at all
# (These should have had summary added by template cleanup)

Filter results:

Exclude Templates/, .obsidian/, .claude/, Archive/, Attachments/
Exclude Daily notes (journals don't need summaries)
If --type specified, filter by frontmatter type
Sort by type for batch efficiency

Phase 2: Generate Summaries (Parallel)

Launch parallel Haiku sub-agents, batching 20 notes per agent:

For each note, the agent should:

Read the full note (frontmatter + body)
Generate a one-line summary following these rules:

Summary Writing Rules

Length: 10-25 words. One sentence. No period at the end
Voice: Active, descriptive. State what the note IS or DOES
Content: Capture the core purpose, not details
Avoid: Starting with "This note...", "A document about...", "Summary of..."
Include: Key entities, technologies, or decisions where relevant

Summary Patterns by Type

Type	Pattern	Example
Concept	What X is	`Continuous Airworthiness Management Organisation responsible for aircraft safety compliance`
Pattern	How to do X	`Event-driven architecture pattern using Kafka for real-time system integration`
Meeting	What was discussed/decided	`Alpha sprint review covering data migration progress and API blockers`
ADR	What was decided and why	`Selected AWS Bedrock over Azure OpenAI for AlertHub safety processing`
Project	What the project delivers	`SAP to DataPlatform data integration enabling unified engineering analytics`
System	What the system does	`MRO Vendor MRO platform managing aircraft maintenance scheduling`
Person	Role and context	`Solutions Architect in Engineering IT, Alpha project lead`
Task	What needs to be done	`Implement Kafka consumer for Alpha work order events`
Incubator	What idea is being explored	`Exploring voice-activated Claude Code workflows for hands-free note capture`
Research	What question was investigated	`Analysis of vault structure identifying efficiency improvements for human and AI workflows`
Reference	What the resource covers/teaches	`AWS documentation on Bedrock guardrails for AI model safety`
Email	What the email communicates	`Proposal to Beta programme board for Claude Code adoption across architecture team`

Return — list of (filepath, summary) tuples

Phase 3: Apply Summaries

For each note with a generated summary:

Read current frontmatter
If summary: null — replace with generated summary (quoted string)
If no summary field — add summary: field after tags
Write updated file using Edit tool

Format:

summary: "Continuous Airworthiness Management Organisation responsible for aircraft safety compliance"

Always quote the summary value since it may contain special YAML characters (colons, brackets).

Phase 4: Report

## Auto-Summary Results

**Notes processed:** {{count}}
**Summaries added:** {{added_count}}
**Notes skipped:** {{skipped_count}} (already has summary or insufficient content)

### By Type
| Type | Summarised | Avg Length |
|------|-----------|------------|
| Concept | 45 | 15 words |
| Meeting | 80 | 18 words |
| ADR | 30 | 20 words |

### Sample Summaries
| Note | Summary |
|------|---------|
| {{note}} | {{summary}} |
| {{note}} | {{summary}} |

Safety

Always use --dry-run first for vault-wide operations
Never overwrite existing non-null summaries
Commit to git before running
If note body is too short (<50 words), skip rather than guess
Summary is additive only — never removes existing summaries

Quality Checks

After running, verify quality by:

Spot-check 10-15 summaries across different types
Ensure summaries are accurate (not hallucinated)
Check length (10-25 words target)
Verify no YAML quoting issues

Related Skills

/summarize — Detailed single-note summarisation
/quality-report — Includes summary coverage metrics
/auto-tag — Companion batch field population skill