view tool fails on large single-line tool output — model never sees actual content

[tsinkai]

Summary

When a custom tool returns large output as a single JSON line (e.g., 55KB), the SDK's large-output handling creates an unrecoverable loop where the model can never access the actual content.

Reproduction

1. Register a custom tool (e.g., KnowledgeSearch) that returns ~55KB of JSON as a single line (common for search/retrieval APIs)
2. The model calls the tool
3. SDK writes the result to a temp file and returns to the model:

   Output too large to read at once (55.3 KB). Saved to: C:\Users\...\copilot-tool-output-xxx.txt
   Consider using tools like grep (for searching), head/tail (for viewing start/end),
   view with view_range (for specific sections), or jq (for JSON) to examine portions of this file.
   

4. Model calls view with view_range=[1, 120] → since the entire content is one line, this returns the whole 55KB line, which gets truncated again:

   [Output truncated. Use view_range=[1, ...] to continue reading.]
   

5. Model calls grep with keyword patterns → every match returns the same giant single line, which also gets redirected to yet another temp file:

   Output too large to read at once (55.4 KB). Saved to: ...copilot-tool-output-yyy.txt
   

6. Model never sees the actual content. It burns 5-8 extra LLM turns trying different view/grep combinations, all hitting the same truncation wall.

What the model actually sees (from LLM request dumps)

Tool Response	Content Length	What model receives
KnowledgeSearch (custom)	845 chars	File path + "use grep/view" message
view (lines 1-120)	66 chars	[Output truncated. Use view_range=[1, ...] to continue reading.]
grep (keyword search)	445 chars	Another file path + "use grep/view" message
view (of grep output)	66 chars	[Output truncated...] again

The model operates essentially blind — it never sees the tool results.

Root Cause

The SDK uses line-based chunking for view (view_range operates on line numbers). When the entire output is a single line, view_range=[1, N] always returns the full content regardless of N, which always exceeds the truncation threshold.

Suggested Fix

• Pretty-print JSON tool output before writing to the temp file (so view_range works on individual lines)
• Or use character-based chunking as fallback when the file has very few lines
• Or allow view to accept a character/byte range for single-line files

Environment

• github-copilot-sdk versions tested: 0.1.23, 0.1.30
• Model: gpt-5.2 (gpt-52-2025-12-11)
• Platform: Windows 11
• Provider: OpenAI (via BYOK)

Impact

Custom tools that return large JSON responses (search APIs, knowledge retrieval, connector actions) are effectively unusable. The model wastes 5-8 extra LLM turns and ultimately answers without having seen the actual data. This is a blocker for agentic workflows that depend on tool-grounded responses.

[SteveSandersonMS]

Thanks @tsinkai. We've tracked this issue in the underlying runtime implemention - it will need to be fixed there.

[garypretty]

@SteveSandersonMS could you provide a link to where this is being tracked in runtime so we can track please? Thanks!