--- before
+++ after
@@ -1,13 +1,9 @@
 #!/usr/bin/env python3
 """Lean, record-only execution, review, and reporting for Codex Replay."""
 
-# This portable plugin must use standard-library HTTP outside the monorepo.
-# ruff: noqa: TID251
-
 from __future__ import annotations
 
 import datetime as dt
-import functools
 import html
 import json
 import math
@@ -15,8 +11,6 @@
 import re
 import stat
 import subprocess
-import time
-import urllib.request
 from dataclasses import asdict, dataclass
 from fractions import Fraction
 from pathlib import Path
@@ -24,8 +18,6 @@
 
 PLUGIN_ROOT = Path(__file__).resolve().parent.parent
 MODEL_PRICING_PATH = PLUGIN_ROOT / "assets" / "model-pricing.json"
-DYNAMIC_PRICING_REFRESH_SECONDS = 60 * 60
-TokenPrices = dict[str, float]
 DEFAULT_CODEX_HOME = Path.home() / ".codex"
 MAX_ARTIFACT_BYTES = 16 * 1024 * 1024
 MAX_REVIEW_CHECK_EXPLANATION_LENGTH = 280
@@ -380,17 +372,6 @@
     """A lean replay execution could not be recorded."""
 
 
-class ModelPrices(TypedDict, total=False):
-    input: float
-    output: float
-    cached_input: float
-    cache_write: float
-    cache_write_5m: float
-    cache_write_1h: float
-    long_context_threshold_input_tokens: int
-    long_context: TokenPrices
-
-
 @dataclass
 class UsageRecord:
     provider: str
@@ -402,6 +383,7 @@
     cache_write_5m_tokens: int = 0
     cache_write_1h_tokens: int = 0
     message_id: str | None = None
+    service_tier: str | None = None
 
 
 @dataclass
@@ -490,6 +472,9 @@
             "status",
             "--porcelain",
             "--untracked-files=normal",
+            "--",
+            ".",
+            ":(top,exclude).replay-tmp",
             check=False,
         )
         if status.returncode == 0:
@@ -581,6 +566,9 @@
             else 0
         ),
         message_id=message_id,
+        service_tier=payload.get("service_tier")
+        if isinstance(payload.get("service_tier"), str)
+        else None,
     )
 
 
@@ -783,6 +771,8 @@
             "--binary",
             baseline_commit,
             "--",
+            ".",
+            ":(top,exclude).replay-tmp",
         )
         diff = tracked.stdout
         names = _git(
@@ -793,6 +783,8 @@
             "--name-only",
             baseline_commit,
             "--",
+            ".",
+            ":(top,exclude).replay-tmp",
         )
         changed.extend(line for line in names.stdout.splitlines() if line)
         untracked = _git(root, "ls-files", "--others", "--exclude-standard", "-z")
@@ -805,6 +797,8 @@
         ]
 
     for relative in sorted(raw_untracked):
+        if Path(relative).parts[0] == ".replay-tmp":
+            continue
         candidate = root / relative
         if candidate.stat().st_size > MAX_ARTIFACT_BYTES:
             continue
@@ -1193,134 +1187,6 @@
     return loaded if isinstance(loaded, dict) else {}
 
 
-def _pricing_rows(document: str, heading: str, columns: Sequence[str]) -> list[dict[str, str]]:
-    in_section = False
-    table: list[list[str]] = []
-    for line in document.splitlines():
-        line = line.strip()
-        if line == heading:
-            in_section = True
-            continue
-        if not in_section:
-            continue
-        if line.startswith("#"):
-            break
-        if line.startswith("|"):
-            table.append([cell.strip() for cell in line.strip("|").split("|")])
-        elif table:
-            break
-    if len(table) < 3 or not set(columns).issubset(table[0]):
-        return []
-    if not all(re.fullmatch(r":?-+:?", cell) for cell in table[1]):
-        return []
-    return [
-        {column: row[index] for index, column in enumerate(table[0])}
-        for row in table[2:]
-        if len(row) == len(table[0])
-    ]
-
-
-def _price_columns(row: Mapping[str, str], columns: Mapping[str, str]) -> TokenPrices | None:
-    prices: TokenPrices = {}
-    for name, column in columns.items():
-        cell = row[column]
-        if cell == "-":
-            continue
-        match = re.fullmatch(r"\$(\d+(?:\.\d+)?)\s*(?:/\s*MTok)?", cell)
-        if match is None:
-            return None
-        price = float(match.group(1))
-        if not math.isfinite(price):
-            return None
-        prices[name] = price
-    return prices if "input" in prices and "output" in prices else None
-
-
-def _parse_first_party_pricing(provider: str, document: str) -> dict[str, ModelPrices]:
-    long_columns: dict[str, str] = {}
-    if provider == "openai":
-        heading = "### Standard pricing data"
-        columns = {
-            "input": "Short context input",
-            "cached_input": "Short context cached input",
-            "cache_write": "Short context cache writes",
-            "output": "Short context output",
-        }
-        long_columns = {
-            name: column.replace("Short context", "Long context")
-            for name, column in columns.items()
-        }
-    elif provider == "anthropic":
-        heading = "## Model pricing"
-        columns = {
-            "input": "Base Input Tokens",
-            "cached_input": "Cache Hits & Refreshes",
-            "cache_write_5m": "5m Cache Writes",
-            "cache_write_1h": "1h Cache Writes",
-            "output": "Output Tokens",
-        }
-    else:
-        return {}
-
-    models: dict[str, ModelPrices] = {}
-    required_columns = ("Model", *columns.values(), *long_columns.values())
-    for row in _pricing_rows(document, heading, required_columns):
-        model = row["Model"].split(" (", 1)[0].strip("`")
-        if provider == "anthropic":
-            match = re.fullmatch(r"Claude ([A-Za-z]+) (\d+(?:\.\d+)?)", model)
-            if match is None:
-                continue
-            family = match.group(1).lower()
-            version = match.group(2).replace(".", "-")
-            if version.split("-")[0] == "3":
-                model = f"claude-{version}-{family}"
-            else:
-                model = f"claude-{family}-{version}"
-        elif re.fullmatch(r"[a-z][a-z0-9.-]+", model) is None:
-            continue
-        standard = _price_columns(row, columns)
-        if standard is None:
-            continue
-        rate: ModelPrices = {"input": standard["input"], "output": standard["output"]}
-        if "cached_input" in standard:
-            rate["cached_input"] = standard["cached_input"]
-        if "cache_write" in standard:
-            rate["cache_write"] = standard["cache_write"]
-        if provider == "anthropic":
-            if len(standard) != len(columns):
-                continue
-            rate["cache_write"] = standard["cache_write_5m"]
-            rate["cache_write_5m"] = standard["cache_write_5m"]
-            rate["cache_write_1h"] = standard["cache_write_1h"]
-        elif any(row[column] != "-" for column in long_columns.values()):
-            long_context = _price_columns(row, long_columns)
-            if long_context is None:
-                continue
-            # OpenAI's standard short/long-context table splits at 272K input tokens.
-            rate["long_context_threshold_input_tokens"] = 272_000
-            rate["long_context"] = long_context
-        models[model] = rate
-    return models
-
-
-def _fetch_dynamic_pricing(provider: str, url: str) -> dict[str, ModelPrices]:
-    refresh_bucket = int(time.monotonic() // DYNAMIC_PRICING_REFRESH_SECONDS)
-    return _cached_dynamic_pricing(provider, url, refresh_bucket)
-
-
-@functools.lru_cache(maxsize=4)
-def _cached_dynamic_pricing(provider: str, url: str, refresh_bucket: int) -> dict[str, ModelPrices]:
-    request = urllib.request.Request(
-        url, headers={"User-Agent": "Codex-Replay/1.0", "Accept": "text/markdown"}
-    )
-    try:
-        with urllib.request.urlopen(request, timeout=5) as response:
-            document = response.read().decode("utf-8")
-    except (OSError, UnicodeError):
-        return {}
-    return _parse_first_party_pricing(provider, document)
-
-
 def _configured_model_name(models: Mapping[str, Any], model: str) -> str | None:
     direct = models.get(model)
     if isinstance(direct, Mapping):
@@ -1334,35 +1200,27 @@
     return None
 
 
-def _configured_rate(models: Mapping[str, Any], model: str) -> Mapping[str, Any] | None:
-    name = _configured_model_name(models, model)
-    if name is not None:
-        candidate = models.get(name)
-        if isinstance(candidate, Mapping):
-            return candidate
-    return None
-
-
-def _dynamic_rate(pricing: Mapping[str, Any], model: str, provider: str) -> ModelPrices | None:
-    provider = {"codex": "openai", "claude": "anthropic"}.get(provider.lower(), provider.lower())
-    sources = pricing.get("dynamic_sources")
-    if not isinstance(sources, Mapping):
+def _configured_rate(models: Mapping[str, Any], record: UsageRecord) -> Mapping[str, Any] | None:
+    provider = {"claude": "anthropic", "codex": "openai"}.get(record.provider, record.provider)
+    identity = (
+        re.sub(r"-\d{8}$", "", record.model.replace(".", "-"))
+        if provider == "anthropic"
+        else record.model
+    )
+    name = _configured_model_name(models, record.model) or _configured_model_name(models, identity)
+    candidate = models.get(name) if name is not None else None
+    if not isinstance(candidate, Mapping) or candidate.get("provider", provider) != provider:
         return None
-    url = sources.get(provider)
-    if not isinstance(url, str) or not url:
+    tier = "fast" if record.service_tier == "priority" else record.service_tier or "standard"
+    if tier != "standard":
+        tiers = candidate.get("tiers")
+        candidate = tiers.get(tier) if isinstance(tiers, Mapping) else None
+    if not isinstance(candidate, Mapping):
+        return None
+    if candidate.get("long_context") is not None and not isinstance(
+        candidate.get("long_context_threshold_input_tokens"), int
+    ):
         return None
-    dynamic_models = _fetch_dynamic_pricing(provider, url)
-    candidate = dynamic_models.get(model)
-    if candidate is None:
-        configured_models = pricing.get("models")
-        if isinstance(configured_models, Mapping):
-            configured_name = _configured_model_name(configured_models, model)
-            if configured_name is not None:
-                candidate = dynamic_models.get(configured_name)
-    if candidate is None and provider == "anthropic":
-        # Pre-4.6 Claude snapshots append a date to the family/version model ID.
-        model_name = re.sub(r"-\d{8}$", "", model.replace(".", "-"))
-        candidate = dynamic_models.get(model_name)
     return candidate
 
 
@@ -1425,13 +1283,8 @@
     models = models if isinstance(models, Mapping) else pricing
     total = 0.0
     missing: list[str] = []
-    dynamic: list[str] = []
     for record in records:
-        rate = _dynamic_rate(pricing, record.model, record.provider)
-        if rate is not None:
-            dynamic.append(record.model)
-        if rate is None:
-            rate = _configured_rate(models, record.model) if isinstance(models, Mapping) else None
+        rate = _configured_rate(models, record) if isinstance(models, Mapping) else None
         if not isinstance(rate, Mapping):
             missing.append(record.model)
             continue
@@ -1445,19 +1298,36 @@
             and isinstance(long_context, Mapping)
         ):
             rate = {**rate, **long_context}
-        total += normalized["ordinary_input_tokens"] * float(rate.get("input", 0)) / 1_000_000
-        total += record.output_tokens * float(rate.get("output", 0)) / 1_000_000
-        total += record.cached_input_tokens * float(rate.get("cached_input", 0)) / 1_000_000
-        cache_rate = rate.get("cache_write", rate.get("cache_write_1h", 0))
-        _, unclassified_cache_write, cache_write_5m, cache_write_1h = _cache_write_breakdown(record)
-        total += unclassified_cache_write * float(cache_rate) / 1_000_000
-        total += cache_write_5m * float(rate.get("cache_write_5m", cache_rate)) / 1_000_000
-        total += cache_write_1h * float(rate.get("cache_write_1h", cache_rate)) / 1_000_000
+        _, unclassified, writes_5m, writes_1h = _cache_write_breakdown(record)
+        write_rate = rate.get("cache_write", rate.get("cache_write_5m"))
+        charges = (
+            (normalized["ordinary_input_tokens"], rate.get("input")),
+            (record.output_tokens, rate.get("output")),
+            (record.cached_input_tokens, rate.get("cached_input")),
+            (unclassified, write_rate),
+            (writes_5m, rate.get("cache_write_5m", write_rate)),
+            (writes_1h, rate.get("cache_write_1h")),
+        )
+        # Native Replay also keeps incomplete prices unknown, rather than charging zero.
+        if any(
+            tokens
+            and (
+                not isinstance(price, (int, float))
+                or isinstance(price, bool)
+                or not math.isfinite(price)
+                or price < 0
+            )
+            for tokens, price in charges
+        ):
+            missing.append(record.model)
+            continue
+        total += sum(tokens * price / 1_000_000 for tokens, price in charges if tokens)
     return {
         "status": "estimated" if not missing else "partial",
         "usd": round(total, 6) if not missing else None,
         "missing_models": sorted(set(missing)),
-        "dynamic_models": sorted(set(dynamic)),
+        "dynamic_models": [],
+        "pricing_as_of": pricing.get("as_of"),
         "basis": "published API-equivalent token pricing",
         "actual_charge": "not observed",
     }

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SHA-256 of public snapshot: 41d0a493722da16a24648dc98ae36d9015457e837dc4119cfc3d93dd1f188d6d

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