attachments

name	attachments
description	Use when the user uploads files or a .zip archive (like user research or logs). Describes how to locate attached files in the sandbox, extract archives if necessary, synthesize findings, and save results back to Mighty.

Attachments

Overview

Use this workflow when a user uploads files (like .zip archives, logs, or documents) and asks you to analyze their contents. The system securely stages attached files directly into your sandbox. It does not automatically unzip archives; you must extract them yourself if needed.

Workflow

1) Locate the attached files

Any files attached to the message are staged in the sandbox. You can locate them by exploring the $MIGHTY_ATTACHMENTS_DIR directory.

Tip: Use ls $MIGHTY_ATTACHMENTS_DIR/files/ to see the exact filenames.

2) Read or Extract

If the file is a regular file (e.g., .log, .csv, .md), you can read it directly:

cat $MIGHTY_ATTACHMENTS_DIR/files/<filename>

If the file is a .zip archive, extract it into a local temporary directory within your sandbox:

mkdir -p /tmp/extracted_files
unzip $MIGHTY_ATTACHMENTS_DIR/files/<filename>.zip -d /tmp/extracted_files

3) Analyze the contents

Iterate over the files or extracted contents. You can use standard tools like ls, cat, jq, and rg to examine the structure and data. If the dataset is large, consider:

• Processing the files in chunks to avoid context limits.
• Synthesizing findings as you go.

4) Save synthesized results

Once you have completed the analysis and synthesized your findings, you MUST persist the results back into the Mighty graph so they are searchable in the future.

Option A: Create a record (Preferred for structured text/learnings) Create a new spec, doc, or decision with your findings:

mt new doc "Research Findings: Q3 User Interviews" --description-file /path/to/your/synthesis.md

Option B: Upload an artifact file (Preferred for large output files like CSVs or combined logs) If your output is a raw file, upload it as a new artifact:

mt file upload /path/to/your/compiled_results.csv

This command returns a reference (e.g., ![[file <file_id>]]) which you can then link to a task or include in a comment.