From akashicrecords
Processes emails (.eml), PDFs, Office docs, images, audio/video by extracting content with mu/markitdown, analyzes intent, suggests AkashicRecords archiving locations per project preferences.
How this skill is triggered — by the user, by Claude, or both
Slash command
/akashicrecords:process-fileThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Generic file processing Skill supporting multiple file formats for parsing and intelligent archiving, fully integrated with the AkashicRecords governance system.
Generic file processing Skill supporting multiple file formats for parsing and intelligent archiving, fully integrated with the AkashicRecords governance system.
Check claude.md:
file-handling-preferences related recordIf no preferences file exists:
file-handling-preferences.md in project rootPreferences file structure:
Detect file type: Determine processing method based on file extension:
| Type | Extension | Processing Tool |
|---|---|---|
| .eml | mu view <filepath> | |
markitdown <filepath> | ||
| Word | .docx | markitdown <filepath> |
| PowerPoint | .pptx | markitdown <filepath> |
| Excel | .xlsx | markitdown <filepath> |
| Image | .jpg, .png, .gif, .webp, .bmp | Read tool (language model direct read) |
| Audio | .mp3, .wav, .m4a, .aac, .ogg | Ask user |
| Video | .mp4, .mov, .avi, .webm | Ask user |
Tool availability check:
mu not installed: Prompt Please install maildir-utils: sudo apt install maildir-utilsmarkitdown not installed: Prompt Please install markitdown: pip install markitdownEmail (.eml):
mu view <filepath>
Extract: sender, recipient, subject, date, body
PDF/Office documents:
markitdown <filepath>
Convert to markdown format
Images: Use Read tool to directly read image, let language model analyze content:
Audio/Video:
Analyze content:
Infer user intent:
Match against preferences:
Use akashicrecords mechanism:
Suggestion logic:
Present analysis results:
## File Analysis Results
**File**: [filename]
**Type**: [file type]
**Content Summary**: [brief summary]
**Inferred Intent**: [archive/update/record]
**Suggested Location**: [target directory path]
**Reason**: [why this location was chosen]
**Planned Operation**:
- Call add-content skill
- Format: [according to RULE.md]
- Filename: [suggested filename]
Do you approve this operation?
Wait for confirmation:
auto_save: true in preferences, can skip confirmationCall corresponding akashicrecords skill:
add-content skillupdate-content skillFormat according to target RULE.md:
Record this processing experience:
### [Date] [File Type]
- Content characteristics: [key features]
- Target location: [actual storage location]
- Processing method: [skill used]
Learning pattern:
When user provides multiple files:
## Multi-File Processing Analysis Results
| # | Filename | Type | Content Summary | Suggested Location | Operation |
|---|----------|------|-----------------|-------------------|-----------|
| 1 | file1.pdf | PDF | [summary] | Research/ | add-content |
| 2 | photo.jpg | Image | [summary] | Personal/ | add-content |
| 3 | email.eml | Email | [summary] | Work/ | add-content |
Please choose:
- Approve all
- Confirm individually
- Cancel
Warning: Cannot process .eml file: mu tool not installed
Please run: sudo apt install maildir-utils
Warning: Unsupported file format: .xyz
How would you like to proceed?
1. Try reading as plain text
2. Record file metadata only
3. Skip this file
Warning: Unable to parse file content
Error: [error message]
How would you like to proceed?
1. Retry
2. Enter summary manually
3. Skip this file
Before operation:
During operation:
After operation:
User: "Read ~/Downloads/transformer-paper.pdf"
Workflow:
markitdown ~/Downloads/transformer-paper.pdfUser: "Archive these emails: email1.eml email2.eml email3.eml"
Workflow:
mu viewUser: "Process this photo ~/Photos/vacation.jpg"
Workflow:
npx claudepluginhub legacybridge-tech/claude-plugins --plugin akashicrecordsBulk imports knowledge from files, directories, or URLs into structured backlogs, or captures a single document with a 5-section template (claims, worth-keeping, contested, action, reaction).
Converts raw files (PDF, docx, images, audio, etc.) into a local Markdown vault with retrieval-friendly frontmatter, then answers questions over it with self-monitoring and MOC proposals.
Processes raw knowledge files (book notes, highlights, raw files) into structured vault notes with metadata extraction, wiki-links, and auto-chaining.