cd /home/daytona/workspace/attachments/6fdc6ce6-f882-4bde-b27c-831b7cb99640 && python3 -c "..."

• cd ... — navigates to a specific directory in the sandbox workspace (where an attachment was uploaded)
• && — only runs the next command if the cd succeeds
• python3 -c "..." — runs a Python snippet inline (the -c flag means "run this string as code")

import pdfplumber

with pdfplumber.open('2.pdf') as pdf:
    for i, page in enumerate(pdf.pages):
        print(f'=== PAGE {i+1} ===')
        print(page.extract_text())

1. import pdfplumber — loads the pdfplumber library, a tool for extracting text and tables from PDFs
2. pdfplumber.open('2.pdf') — opens the file 2.pdf in the current directory (the with block ensures the file is closed cleanly afterward)
3. enumerate(pdf.pages) — iterates over every page with an index (i)
4. print(f'=== PAGE {i+1} ===') — prints a separator header for each page (1-indexed)
5. page.extract_text() — extracts all readable text from that page and prints it

cd /home/daytona/workspace/attachments/... && python3 -c "..." 2>&1

• Same directory navigation and inline Python as before
• 2>&1 — redirects stderr (error messages) into stdout, so both normal output and errors appear together in the terminal

from pypdf import PdfReader
import base64

reader = PdfReader('2.pdf')
page2 = reader.pages[1]

• Uses pypdf (a different PDF library than pdfplumber — lower-level, closer to the raw PDF spec)
• reader.pages[1] — gets page 2 (0-indexed, so index 1 = second page)
• base64 is imported but not actually used in this snippet (likely a leftover)

if '/Resources' in page2:
    res = page2['/Resources']
    print('Resources keys:', list(res.keys()) if hasattr(res, 'keys') else res)
    if '/XObject' in res:
        xobj = res['/XObject']
        print('XObjects:', list(xobj.keys()))

from pypdf import PdfReader
reader = PdfReader('2.pdf')
page2 = reader.pages[1]
res = page2['/Resources']
xobj = res['/XObject']

img = xobj['/Im1']

• From the previous step, the names of embedded objects were discovered (e.g. Im0, Im1, etc.)
• This picks /Im1 specifically — the second embedded image on that page
• img is now a PDF stream object representing that image

print('Type:', img.get('/Subtype'))
print('Filter:', img.get('/Filter'))
print('Width:', img.get('/Width'))
print('Height:', img.get('/Height'))

data = img.get_data()
with open('/tmp/ultrasound.jpg', 'wb') as f:
    f.write(data)
print('Saved image, size:', len(data), 'bytes')

• img.get_data() — decompresses and returns the raw image bytes
• open(..., 'wb') — opens a file for writing in binary mode (wb)
• Writes the bytes to /tmp/ultrasound.jpg
• Prints the file size in bytes as confirmation

Key Differences

1. Different PDF file (different directory)

• Previous commands: attachments/6fdc6ce6-...
• This command: attachments/a1861630-...

2. High-level API vs. low-level manual navigation

3. Loops over ALL pages and ALL images

for i, page in enumerate(reader.pages):         # every page
    for img in page.images:                      # every image on that page

4. Naming the output files dynamically

open(f'/tmp/page{i+1}_img.png', 'wb')

• Saves each image as page1_img.png, page2_img.png, etc.
• Previous script saved to a hardcoded /tmp/ultrasound.jpg
• Note: it saves everything as .png regardless of actual format — fine for writing raw bytes, but the extension may be misleading if the source was JPEG

5. base64 and io imported but unused

Summary

Deep Dive: The Two Points

1. Saving as .png regardless of actual format

What a file extension actually is

with open(f'/tmp/page{i+1}_img.png', 'wb') as f:
    f.write(img.data)

Why this matters in practice

• Most image viewers are smart enough to read the magic bytes and open the file correctly anyway, ignoring the extension
• Some software (especially older tools, APIs, or scripts) trusts the extension blindly and may fail or misinterpret the file
• A JPEG saved as .png will often be larger than expected when re-saved, because software might re-encode it as a true PNG

The correct approach

for img in page.images:
    # img.name often includes the real extension, e.g. 'Im1.jpg'
    ext = img.name.split('.')[-1] if '.' in img.name else 'bin'
    with open(f'/tmp/page{i+1}_img.{ext}', 'wb') as f:
        f.write(img.data)

def get_ext(data):
    if data[:3] == b'\xff\xd8\xff':
        return 'jpg'
    elif data[:4] == b'\x89PNG':
        return 'png'
    else:
        return 'bin'  # unknown, safe fallback

2. base64 and io imported but unused

What they are

import base64
data = b'\xff\xd8\xff'          # raw JPEG bytes
encoded = base64.b64encode(data)
# → b'/9j/'  (safe ASCII string)

import io
buffer = io.BytesIO(img.data)   # treat image bytes as a virtual file
from PIL import Image
image = Image.open(buffer)      # open it with Pillow without saving to disk

Why they're in the script but unused

Why it's harmless but worth cleaning up

• Unused imports don't cause errors or slow down the script meaningfully
• They do add confusion — a reader assumes base64 and io are used somewhere and wastes time looking
• Python linters (pylint, flake8, ruff) flag these as F401 errors: "imported but unused"
• Clean code would remove them:

# Remove this:
import base64, io

# Keep only what's actually used:
from pypdf import PdfReader

The Problem: File Extension Mismatch in Image Extraction

What the AI agent wrote

from pypdf import PdfReader
reader = PdfReader('2.pdf')
page2 = reader.pages[1]
res = page2['/Resources']
xobj = res['/XObject']
img = xobj['/Im1']

data = img.get_data()
with open('/tmp/ultrasound.jpg', 'wb') as f:
    f.write(data)

from pypdf import PdfReader
import base64, io  # imported, never used

reader = PdfReader('2.pdf')
for i, page in enumerate(reader.pages):
    for img in page.images:
        with open(f'/tmp/page{i+1}_img.png', 'wb') as f:
            f.write(img.data)

The Core Problem

Why the Agent Does This

• When writing to a file, a name and extension must be chosen — the agent picks something plausible
• In Script 1, the surrounding context (medical PDF, word "ultrasound") biased the agent toward .jpg
• In Script 2, the agent needed a single extension for a loop covering unknown images — .png was chosen as a generic default
• Neither script was instructed to verify — so neither did

Why This Matters for Your Harness

• Reject the file as malformed
• Attempt to decode it as PNG and fail
• Pass silently but produce wrong metadata (dimensions, color space, etc.)

What to Tell Your Coding Agent

When extracting image data from any source (PDF, archive, database, API response, etc.) and writing it to disk, the file extension must always be derived from the actual byte content, not assumed from context, inferred from variable names, or defaulted to a generic format. Extension assignment is not a cosmetic step — it is a correctness requirement.