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claude-code - 💡(How to fix) Fix Auto-downscale/summarize images to avoid 2000px many-image error

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Claude Code fails mid-session with:

An image in the conversation exceeds the dimension limit for many-image requests (2000px). Run /compact to remove old images from context, or start a new session.

This happens even when the context window is at ~10-20% used, so /compact is an overreaction — it wipes useful text history just to shed one oversized image. The limit is about image dimensions, not context size, but the user-facing remedy conflates the two.

Error Message

Agentic use cases (mobile MCP, browser automation, visual research loops) are exactly where Claude Code's agent loop shines — and also where this error hits hardest and earliest. The fix is local to Claude Code (resize before send); no API change required.

Root Cause

Agentic use cases (mobile MCP, browser automation, visual research loops) are exactly where Claude Code's agent loop shines — and also where this error hits hardest and earliest. The fix is local to Claude Code (resize before send); no API change required.

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Summary

Claude Code fails mid-session with:

An image in the conversation exceeds the dimension limit for many-image requests (2000px). Run /compact to remove old images from context, or start a new session.

This happens even when the context window is at ~10-20% used, so /compact is an overreaction — it wipes useful text history just to shed one oversized image. The limit is about image dimensions, not context size, but the user-facing remedy conflates the two.

Repro

Common agentic workflows that trigger this quickly:

  • Device automation via MCP servers (each step = a fresh screenshot)
  • Browser automation / visual web research (many page screenshots)
  • Any loop where the model iteratively captures screenshots and acts on them

Expected behavior

Claude Code should handle this on ingest, without user intervention:

  1. Auto-downscale any incoming image to ≤2000px on its longest edge before appending it to the conversation. The API limit is known and fixed — there's no reason Claude Code should ever forward an image that will fail.
  2. (Stretch) After N images accumulate, auto-summarize older screenshots to text and drop the image bytes, so long agentic runs don't silently degrade or suddenly die.

Actual behavior

The request fails outright and the user is told to /compact, which also discards text history they may still need. In agentic loops this is especially bad because the model itself doesn't proactively summarize-and-drop older screenshots — it just keeps stacking them until the API rejects the call.

Why this matters

Agentic use cases (mobile MCP, browser automation, visual research loops) are exactly where Claude Code's agent loop shines — and also where this error hits hardest and earliest. The fix is local to Claude Code (resize before send); no API change required.

Environment

  • Platform: Windows 11
  • Model: Claude Opus 4.7 (1M context)
  • Trigger: agentic screenshot-heavy session; context still well under 50%

extent analysis

TL;DR

Implement auto-downscaling of incoming images to ≤2000px on their longest edge before appending them to the conversation to prevent dimension limit errors.

Guidance

  • Identify the point of image ingestion in the Claude Code workflow and modify it to resize images to ≤2000px on their longest edge using an image processing library.
  • Consider implementing a queue or buffer to handle images that exceed the dimension limit, allowing for resizing before forwarding to the API.
  • Review the agentic workflow loops that trigger this issue, such as device automation via MCP servers and browser automation, to ensure that image resizing is applied consistently.
  • Evaluate the feasibility of implementing auto-summarization of older screenshots to text after a certain number of images accumulate, as a stretch goal to further improve performance.

Example

from PIL import Image

def resize_image(image_path):
    img = Image.open(image_path)
    max_size = 2000
    if max(img.size) > max_size:
        scale = max_size / max(img.size)
        new_size = (int(img.size[0] * scale), int(img.size[1] * scale))
        img = img.resize(new_size)
    img.save(image_path)

Note: This example uses the Python Imaging Library (PIL) to resize an image, but the actual implementation will depend on the programming language and libraries used in Claude Code.

Notes

The proposed solution focuses on resizing images before appending them to the conversation, which should prevent the dimension limit error. However, implementing auto-summarization of older screenshots to text may require additional development and testing.

Recommendation

Apply the workaround of auto-downscaling incoming images to ≤2000px on their longest edge, as it directly addresses the root cause of the issue and can be implemented locally within Claude Code without requiring API changes.

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FAQ

Expected behavior

Claude Code should handle this on ingest, without user intervention:

  1. Auto-downscale any incoming image to ≤2000px on its longest edge before appending it to the conversation. The API limit is known and fixed — there's no reason Claude Code should ever forward an image that will fail.
  2. (Stretch) After N images accumulate, auto-summarize older screenshots to text and drop the image bytes, so long agentic runs don't silently degrade or suddenly die.
#api#API routing#API middleware#SSR setup#ISR setup

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claude-code - 💡(How to fix) Fix Auto-downscale/summarize images to avoid 2000px many-image error