inbox-processor

dakesan's avatarfrom dakesan

This skill should be used when processing files in the inbox/ directory, organizing unstructured input, classifying content, or extracting actionable information. Triggered by requests like "process inbox", "organize inbox files", "classify this memo", or "inbox を整理".

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[Document Processing]

When & Why to Use This Skill

The Inbox Processor is a powerful Claude skill designed to automate the organization of unstructured data and files. It specializes in classifying content, extracting actionable insights such as decisions and tasks, and routing information to appropriate destinations. By transforming a cluttered 'inbox' into a structured knowledge base, it significantly enhances workflow efficiency and ensures no critical information is lost.

Use Cases

  • Automated File Organization: Automatically scan and classify diverse files in an inbox directory into categories like Meeting Notes, Protocols, and Research Data.
  • Actionable Information Extraction: Parse unstructured meeting records to identify key decisions, assignable action items, and follow-up questions for project tracking.
  • Knowledge Base Integration: Streamline the transition of raw research ideas and literature notes into formatted entries within a structured lab notebook or wiki.
  • Project Management Updates: Automatically update steering documents and task lists (e.g., tasks.md) based on the content of processed memos and reports.
  • Batch Processing: Efficiently handle high volumes of incoming documents by applying consistent classification and extraction rules across multiple files simultaneously.
nameinbox-processor
descriptionThis skill should be used when processing files in the inbox/ directory, organizing unstructured input, classifying content, or extracting actionable information. Triggered by requests like "process inbox", "organize inbox files", "classify this memo", or "inbox を整理".

Inbox Processor

Overview

Processes and organizes unstructured input files from the inbox/ directory. Classifies content, extracts actionable information, and suggests appropriate destinations for integration into the research workflow.

Core Capabilities

1. File Classification

Classify inbox files into categories based on content.

Categories:

  1. Meeting Notes: Discussion records, decisions, action items
  2. Protocols: Experimental procedures, SOPs
  3. Ideas: Research ideas, hypotheses, brainstorming
  4. Data: Raw data files, datasets
  5. Literature: Papers, references, reading notes
  6. Miscellaneous: Unclear or mixed content

Workflow:

  1. Read file from inbox/
  2. Analyze content to determine category
  3. Extract key information
  4. Suggest destination
  5. Optionally move/process file

2. Information Extraction

Extract actionable information from unstructured content.

What to extract:

From Meeting Notes:

  • Decisions made
  • Action items (who, what, when)
  • Key discussion points
  • Follow-up questions

From Protocols:

  • Procedure steps
  • Required materials
  • Expected outcomes
  • Citations/sources

From Ideas:

  • Core hypothesis
  • Experimental approach
  • Required resources
  • Potential experiments

From Literature:

  • Key findings
  • Relevant methods
  • Citations
  • Relevance to current work

3. Destination Suggestions

Recommend where content should be integrated.

Classification Rules (from references/classification-rules.md):

Content Type Suggested Destination Rationale
Meeting notes notebook/knowledge/meeting_YYYY-MM-DD.md Reusable context
Protocol notebook/knowledge/protocol_[name].md Reusable procedure
Experiment idea Create new lab notebook via /research-exp Start experiment
Research hypothesis Refine with hypothesis-driven skill Improve quality
Raw data file data/raw/[filename] Data storage
Literature notes notebook/knowledge/literature_[topic].md Reference material

4. Integration Actions

After classification, take appropriate action.

Possible actions:

  1. Move to knowledge/:

    mv inbox/meeting_notes.txt notebook/knowledge/meeting_2025-01-15.md

  2. Create experiment:

    Content suggests new experiment → Use /research-exp

  3. Add to STEERING.md:

    Important decisions → Update priorities in STEERING.md

  4. Add to tasks.md:

    Action items → Add to notebook/tasks.md

  5. Process for report:

    Relevant findings → Note in ongoing report

  6. Archive:

    mv inbox/old_file.txt inbox/archive/

Usage Workflow

Typical Usage

  1. User adds file to inbox/:

    User: "I put meeting notes in inbox/team_meeting.md"

  2. Classify content:

    Assistant reads file, determines category: Meeting Notes

  3. Extract information:

    Decisions:
- Approved Exp04 (ATAC-seq analysis)
- Prioritize cell cycle validation

Action items:
- [User] Design primers for qPCR by Friday
- [Collaborator] Share ChIP-seq data next week

Discussion:
- Considered three-prime seq vs bulk RNA-seq
- Decided bulk more appropriate for current question

  4. Suggest destination:

    Suggested destination: notebook/knowledge/meeting_2025-01-15.md
Suggested actions:
- Add primer design to tasks.md
- Update STEERING.md with Exp04 approval
- Plan to receive ChIP-seq data

  5. Implement (with user approval):

    Move file, update tasks.md, update STEERING.md

Batch Processing

Process multiple inbox files:

User: "Process all files in inbox/"