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+# Lint a request for cross-provider portability before a LiteLLM provider swap
+
+[LiteLLM](https://github.com/BerriAI/litellm) standardizes the *call* -- one
+`completion()` signature across OpenAI, Anthropic, Gemini, Bedrock, and more.
+It does not check whether the *content* of your messages/params (a hardcoded
+"as an OpenAI assistant" system prompt, a provider-specific stop-sequence
+limit, a temperature outside the target provider's accepted range, a leaked
+chat-template token) will still behave correctly once you point `model=` at
+a different provider.
+
+[`prompt-portability`](https://github.com/nac7/prompt-portability) is an
+open-source CLI/library that lints exactly that gap. This example lints a
+request before handing it to `litellm.completion()`.
+
+## Run it
+
+```bash
+pip install prompt-portability litellm
+python check_before_provider_swap.py
+```
+
+## What it does
+
+1. Builds a request payload written and tested against OpenAI.
+2. Runs `prompt-portability`'s linter against it, surfacing portability
+   issues that would only otherwise show up once the request actually hits
+   a different provider.
+3. Calls `litellm.completion()` with the same payload (mocked, so no API key
+   is needed to run this example) to show LiteLLM's own call succeeds
+   regardless -- confirming these are issues LiteLLM's translation layer
+   does not catch on its own.
diff --git a/cookbook/prompt_portability_check/check_before_provider_swap.py b/cookbook/prompt_portability_check/check_before_provider_swap.py
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+"""
+Lint a request payload for cross-provider portability *before* handing it to
+LiteLLM.
+
+LiteLLM standardizes the *call* -- one `completion()` signature that routes
+to OpenAI, Anthropic, Gemini, Bedrock, etc. It does not, however, check
+whether the *content* of your messages/params is actually safe to send to
+every provider behind that call. Things like:
+
+  - a system prompt that hardcodes "As an OpenAI language model..."
+  - a stop_sequences list with 5 entries (OpenAI caps this at 4)
+  - a temperature of 2.5 (outside Anthropic/Gemini's accepted range)
+  - a chat-template special token leaked from a different model family
+
+...will pass straight through LiteLLM's translation layer and fail (or
+silently misbehave) only once they hit the target provider's API.
+`prompt-portability` catches these before the call is made, so a provider
+swap in your LiteLLM `model=` string doesn't surface a portability bug at
+runtime.
+
+Install:
+    pip install prompt-portability litellm
+
+Run:
+    python check_before_provider_swap.py
+"""
+
+from __future__ import annotations
+
+import litellm
+from llm_prompt_lint.linter import lint
+from llm_prompt_lint.parsers import detect_and_parse
+
+request = {
+    "model": "gpt-4o",
+    "messages": [
+        {
+            "role": "system",
+            "content": "You are a helpful assistant. As an OpenAI assistant, "
+            "always answer in a formal tone.",
+        },
+        {"role": "user", "content": "Summarize this quarter's RAG index drift report."},
+    ],
+    "temperature": 2.5,
+    "stop": ["\n\n", "END", "###", "STOP", "<|end|>"],
+}
+
+doc = detect_and_parse(request)
+report = lint(doc)
+
+print(f"prompt-portability found {len(report.findings)} portability issue(s):\n")
+for finding in report.findings:
+    print(f"  [{finding.rule_id}] {finding.message}")
+
+if report.findings:
+    print(
+        "\nFix these before swapping providers -- e.g. via LiteLLM's "
+        "`model=\"anthropic/claude-...\"` -- to avoid a runtime surprise on "
+        "the new provider."
+    )
+
+response = litellm.completion(
+    model="gpt-4o",
+    messages=request["messages"],
+    temperature=request["temperature"],
+    stop=request["stop"],
+    mock_response="This call succeeds even though the payload above has "
+    "portability issues LiteLLM doesn't check.",
+)
+print(f"\nLiteLLM call (mocked) still went through: {response.choices[0].message.content!r}")