The ghost in the machine #
We were testing routine web work: filling forms, down files, and verifying data. I was using two different setups. One hit the computer use API directly, and the other used Claude Code in headless mode (claude -p
) paired with Playwright.
To keep things objective, we used machine verification. We didn't trust the agent's "I'm done" message; we checked the actual JSONL payloads and file sizes. When the headless setup started failing almost every single trial, my first instinct was that the model was just choking on the specific prompt format. I was wrong. The model wasn't the problem—the Windows environment was.
The culprit is the .CMD shim #
If you're on Windows and installed Claude Code via npm, you've got a file called claude.CMD
sitting on your PATH. When you use Python's subprocess
or shutil.which("claude")
, Windows resolves to that .CMD
file instead of the actual executable.
That file is just a batch wrapper:
"%dp0%\node_modules\@anthropic-ai\claude-code\bin\claude.exe" %*
Here is the catch: when you pass a multi-line prompt through that %*
argument forwarder in cmd.exe
, everything after the first newline is silently deleted. The agent doesn't get an error; it just receives a truncated prompt. In my tests, the agent would see "Follow the instruction below exactly," and then nothing. Of course, it failed because the actual instructions were on line two.
I put together this snippet to prove it. If you run this, you'll see the shim fails while the direct .exe
works:
import os, subprocess
EXE = os.path.join(os.environ["APPDATA"], "npm", "node_modules",
"@anthropic-ai", "claude-code", "bin", "claude.exe")
CMD = os.path.join(os.environ["APPDATA"], "npm", "claude.CMD")
PROMPT = "Follow the instruction below exactly.\nOutput the string MARKER_TAIL_9137 and nothing else."
for label, argv0 in (("claude.CMD (shim)", CMD), ("claude.exe (direct)", EXE)):
r = subprocess.run([argv0, "-p", PROMPT], capture_output=True, text=True,
encoding="utf-8", errors="replace", timeout=180)
out = (r.stdout or "") + (r.stderr or "")
print(label, "tail_received =", "MARKER_TAIL_9137" in out)
How to fix your AI workflow #
This is a nightmare to debug because there are no crash logs or non-zero exit codes. Everything looks "fine," but your agent is basically operating with amnesia. If you're building a real-world deployment on Windows, you have two options to avoid this:
Call the binary directly: Don't trustshutil.which
. Explicitly point your code toclaude.exe
.Flatten your prompts: Replace all newlines with spaces before passing the string to the CLI. This is the safer bet for cross-platform stability.
For anyone doing deep dive prompt engineering, just remember that the "plumbing" between your Python script and the LLM can be just as volatile as the model itself.
Next Claude Code managed to polish our internal agent using a $10k →
All Replies （3） #
@ChrisPunkProbably just another case of lazy dev work. Why would it even work on Linux but not Windows?