#!/usr/bin/env python3
"""
llm-chat converter output must carry NO Codex pins.

Uses the real proof-checker / experiment-audit / research-review sources as
fixtures (the skills with the densest reviewer payloads): after
convert_content(), no OpenAI model pin, no model_reasoning_effort knob, and no
mcp__codex__ tool name may survive — a leftover pin would be sent verbatim to a
generic OpenAI-compatible backend that rejects or misroutes it.

Run: python3 tests/test_llm_chat_converter.py   (also pytest-compatible)
"""
import os
import re
import sys

REPO = os.path.join(os.path.dirname(os.path.abspath(__file__)), "..")
sys.path.insert(0, os.path.join(REPO, "tools"))
from convert_skills_to_llm_chat import convert_content  # noqa: E402

FIXTURES = [
    "skills/proof-checker/SKILL.md",
    "skills/experiment-audit/SKILL.md",
    "skills/research-review/SKILL.md",
    "skills/result-to-claim/SKILL.md",
    "skills/kill-argument/SKILL.md",
    "skills/interview-cheatsheet/SKILL.md",
    "skills/patent-review/SKILL.md",
    "skills/render-html/SKILL.md",
    "skills/auto-review-loop/SKILL.md",
]
FORBIDDEN = re.compile(r"mcp__codex__|model_reasoning_effort|model_#|model:\s*[\"'`]?gpt-|model:\s*REVIEWER_MODEL")


def offending_lines(path):
    src = open(os.path.join(REPO, path), encoding="utf-8").read()
    out = convert_content(src)
    bad = []
    for i, line in enumerate(out.split("\n"), 1):
        if "mcp__manual_review" in line:   # separate MCP, not a Codex pin
            continue
        if FORBIDDEN.search(line):
            bad.append(f"{path} (converted) line {i}: {line.strip()[:100]}")
    return bad


def test_converted_output_has_no_codex_pins():
    problems = []
    for f in FIXTURES:
        problems += offending_lines(f)
    assert not problems, "\n".join(problems)


if __name__ == "__main__":
    ps = []
    for f in FIXTURES:
        ps += offending_lines(f)
    if ps:
        print("\n".join(ps))
        sys.exit(1)
    print(f"ok: {len(FIXTURES)} fixtures convert clean")